accelerating the transformation to manufacturing 4.0 2018 ...€¦ · 1 14th annual manufacturing...
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T H E M A N U F A C T U R I N G L E A D E R S H I P C O U N C I L
www.mlsummit.com
June 11 - 13, 2018 | Hyatt Regency Huntington Beach Resort and Spa | Huntington Beach, CA
14th Annual
M a n u f a c t u r i n g L e a d e r s h i p S umm i tF e a t u r i n g t h e 2 0 1 8 M a n u f a c t u r i n g L e a d e r s h i p A w a r d s G a l a
Accelerating the Transformation to Manufacturing 4.0
2018 EXECUTIVE CHRONICLES
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14th Annual Manufacturing Leadership Summit Accelerating the Transformation to Manufacturing 4.0
Dear Colleague:
At the 14th Annual Manufacturing Leadership Summit, Frost and Sullivan convened top
industry leaders to discuss the ideas and technologies that are shaping the future of
manufacturing today. In particular, participants explored the need to accelerate their
organization’s transformation to Manufacturing 4.0, or M4.0. Throughout, we noted key
ideas and best practices discussed in the sessions to create the Manufacturing
Leadership Summit Chronicles. This e-book collection includes the most valuable
insights and take-aways from the event.
Readers will learn from Brynn Watson, Vice President, Future Enterprise Program,
Corporate Engineering and Program Operations, Lockheed Martin Corporation, who
discussed Manufacturing 4.0 Transformation in Action; Stephen Engel, Senior Vice
President, Strategic Solutions Leader, Americas Hitachi Consulting, who examined
Leadership in the Digital Age; and Caralynn Nowinski Collens, Chief Executive Officer,
UI Labs, and Member, Manufacturing Leadership Council, who explored The Future of
Work in the Manufacturing 4.0 Era.
Why not harness the latest thinking shared at the 14th Annual Frost & Sullivan
Manufacturing Leadership Summit to create and sustain a competitive advantage at
your organization? These Manufacturing Leadership Summit Chronicles were
compiled to help you identify and address the tactical and strategic issues facing the
manufacturing community today.
Thank you for your participation in this Frost & Sullivan event. I look forward to our
continued partnership and welcome any feedback you may have on the Manufacturing
Leadership Chronicles.
Sincerely,
David Brousell
Co-Founder, Global Vice President and Editorial Director
Manufacturing Leadership | Frost & Sullivan
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TABLE OF CONTENTS Tuesday, June 12, 2018 OPENING ADDRESS Picking Up the Pace Of Manufacturing 4.0 ......................................................................... 4
KEYNOTE-with video link Manufacturing 4.0 Transformation in Action ..................................................................... 7
CASE STUDY Cyber in the Age of Digital Manufacturing ........................................................................10
MANUFACTURING LEADERSHIP AWARDS SPOTLIGHT Selected Winners of the 2018 Manufacturing Leadership Awards ................................13
CONCURRENT COLLABORATION ZONES – THINK TANKS Zone 1. Manufacturing 4.0: Where do I Begin? ...............................................................16
CONCURRENT COLLABORATION ZONES – THINK TANKS Zone 2. Applying Artificial Intelligence and Machine Learning for Competitive Advantage ...............................................................................................................................20
CONCURRENT COLLABORATION ZONES – THINK TANKS Zone 3. Building Your Digital Enterprise ..........................................................................27
CONCURRENT COLLABORATION ZONES – THINK TANKS Zone 4. A Manufacturing 4.0 Roadmap for Legacy Assets ............................................30
CONCURRENT COLLABORATION ZONES – THINK TANKS Zone 5. Using the IoT to Elevate Supply Chain Visibility ...............................................35
CASE STUDY Embarking on the Manufacturing 4.0 Journey .................................................................38
EXECUTIVE INSIGHTS-with video link An SMB’s M4.0 Cultural Transformation ............................................................................41
KEYNOTE-with video link Leadership in the Digital Age ..............................................................................................45
PANEL DISCUSSION SMB Perspectives on Manufacturing 4.0 ...........................................................................49
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Wednesday, June 13, 2018 KEYNOTE The Future of Work in the Manufacturing 4.0 Era ...........................................................53
EXECUTIVE INSIGHTS New Insights into the Leader’s Role in Driving Safety Excellence ................................56
MANUFACTURING LEADERSHIP AWARDS SPOTLIGHT Selected Winners of the 2018 Manufacturing Leadership Awards ................................59
CONCURRENT COLLABORATION ZONES - THINKTANKS Zone 1. Digital Twin Deployment – You Aren’t Alone .....................................................63
CONCURRENT COLLABORATION ZONES - THINKTANKS Zone 2. Edge Computing in Manufacturing 4.0 ...............................................................67
CONCURRENT COLLABORATION ZONES - THINKTANKS Zone 3. A Renaissance in Product Design and Manufacturing: The New Role of Generative Design .................................................................................................................70
CONCURRENT COLLABORATION ZONES – THINKTANKS Zone 4. Optimizing Assets through Predictive Maintenance ..........................................73
CONCURRENT COLLABORATION ZONES – THINKTANKS Zone 5. Will Blockchain Transform Your Supply Network? ............................................76
EXECUTIVE INSIGHTS Blueprint for Disrupting Your Culture and Turning Employees into Innovators .........80
BOARD OF GOVERNORS PANEL DISCUSSION Factories of the Future .........................................................................................................84
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______________________________________________________________________
OPENING ADDRESS Picking Up the Pace of Manufacturing 4.0
PRESENTER
David Brousell, Co-Founder, Global Vice President and Editorial Director
Manufacturing Leadership Council, Frost & Sullivan
LinkedIn Profile
TIME
Tuesday, June 12, 2018 at 8:10 am
______________________________________________________________________
SESSION ABSTRACT
In the last few years, the manufacturing industry has come to realize that the journey to
Manufacturing 4.0 is a complex undertaking, with technological change only one part of
the transition. The more difficult parts, it turns out, are at the leadership, cultural, and
organizational levels. The key question facing manufacturing executives is: how to deal
with the multi-dimensional challenge of M4.0 and accelerate the embrace of the new
paradigm?
KEY TAKE-AWAYS
Insight on what it means to be a “digital” leader
Examples of the most important elements of a digital culture
Key factors to best organize around the M4.0 opportunity
INTRODUCTION
The Manufacturing Leadership Council Mission: To enable manufacturing leaders to
imagine a better future and to make it a reality. Other guiding principles: Connect,
participate, learn, network, benchmark, teach, engage, and inspire!
Speaker David Brousell: This is the 14th time I have presided over this event. Fourteen
years ago, the theme was progressive manufacturing. Since then, we’ve seen economic
upturns and downtowns, disruptive business transformations, war, globalization of
markets, price reductions, new technologies, IT and OT challenges, the need for greater
agility, leadership challenges and much more.
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KEY INSIGHT
Today, manufacturing is positioned to be the driver of economic and social prosperity.
Our goal is not to make things, but to make life better for all people.
We seek to drive innovation through three key dimensions of Manufacturing 4.0:
1. Technology to create information intensive factories and plants
2. The organization of flatter, more collaborative structures where decision making
is pushed down the line
3. Leadership challenges of creating and driving a digital business
The above requires us to think differently about ourselves, our organizations, and our
industry: “The greatest danger in times of turbulence is not the turbulence; it is to act
with yesterday’s logic.” – Peter Drucker
The pattern of change of M4.0 is not necessarily linear, but momentum is always
accelerating. More realistically, the pattern of change can resemble a two steps forward
one step backward scenario including testing, failing, learning and continuing. Clearly,
manufacturing has gone through transformation before. What is different this time is the
SPEED of change. All is faster than ever before. We write this new era in real time.
The idea of digital reinvention is taking place in corporate boardrooms all around the
world:
M4.0 is an opportunity to reinvent your company for the future. For example:
Voss in France - took up M4.0 technologies, now it is a benchmark plant for
transformation
M4.0 is now an international competitiveness issue of the highest order. M4.0
initiatives and projects are underway around the world. Greater efforts and
roadmaps are being made
The countries whose companies are most successful with M4.0/digital
economies will be the dominant powers of the 21st century and beyond
We have entered a new phase of M4.0. Leadership in this ever-changing digital arena
requires new approaches including being open to using data analytics and constant
connectivity. There is a high degree of emphasis on technical competencies such as
computer based analytics for data driven decisions, simulation and modeling.
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But the most fundamental challenges are around changing corporate cultures to align
with the new realities of the digital era and change processes for the new digital
paradigm.
Most manufacturers have moved beyond the ‘awareness’ stage of M4.0 to the active phase.
TAKE-AWAY
The biggest need is to MIGRATE BUSINESS to M4.0:
1. Think big about M4.0 go for breakthroughs in products and delighting customers
2. Develop an M4.0 based business strategy
3. Explore new business models that can make you a market disrupter
4. Create a culture of M4.0 innovation and success; cultivate risk-taking
5. Embrace insights from M4.0 technologies esp. data analytics
6. Create collaborative cross-functional teams employees, customers
7. Diversify workforce and leadership, bring in more women! Bring in veterans
8. Develop digital acumen in your leadership team talk the talk walk the walk-then
run
9. Be careful about applying conventional ROI metrics too fast. Try to learn first
ACTION ITEM
Leadership in the digital era:
Rely on data analysis more than intuition/experience
Create a fact-driven culture of decision making
Be ready for change-70% of participants indicated their teams are ready for the
change
FINAL THOUGHT
A leader’s job is to look into the future and see the organization not as it is, but as it
should be. Remember, as an industry, we (manufacturers) play a major role in people’s
lives. It is in our power to create a better world. It all starts with imagination.
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______________________________________________________________________
KEYNOTE Manufacturing 4.0 Transformation in Action
PRESENTER
Brynn Watson, Vice President, Future Enterprise Program
Digital Transformation Office, Lockheed Martin Corporation
LinkedIn Profile
TIME
Tuesday, June 12, 2018 at 8:30am
______________________________________________________________________
View video here: https://vimeo.com/frostsullivan/review/273734686/8dd58cd358
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INTRODUCTION
Lockheed Martin takes a holistic approach to digital transformation examining the entire
manufacturing life cycle. As a global security and aerospace company, they have
100,000 employees -- 49,000 are scientists and engineers. To transform incredibly
innovative technologies to scale requires big scope of work.
OVERVIEW
Brynn emphasized that the era we’re now entering requires an investment in the “what”
more than the “how” – the boundaries push the journey. This demands that you look at
the entire cycle of manufacturing in order to transform products. Furthermore, you must
empower small teams to come together to initiate solutions.
At Lockheed Martin, the company whole-heartedly embraces digital technologies such
as robotics and data analytics as key technologies of a new production era. This
mandates an attack plan for rescaling and exploring how digital technologies impact the
human machine.
TAKE AWAY
Lockheed Martin uses robotics automation with non-manufacturing processes,
too. But now virtual reality (VR) improves performance of manufacturing process. So,
they ask, how can this technology be maximized? How to take these technologies to
scale? They are partnering with customers to make these changes happen and
leveraging internet and microprocessor technologies. Lockheed Martin is also well
equipped to come up with solutions fast because of generative design.
Brynn noted that one of the greatest assets fueling advanced technology is the
people. The competition for talent is fierce, because there’s a shortage of skilled or
experienced workers. Currently, millennials are 30% of the population and will soon be
70% of the workforce. This generation’s point of view is unique when it comes to the
workplace. They want transparency, meaningful work, and they want to be heard. They
also want to know what’s going on elsewhere in the corporation.
We must celebrate diversity in the workforce, utilize every brain. At the same time,
training and recruiting need to be re-imagined. There needs to be a new mindset about
recruiting practices and we must look at different partners besides universities. The
millennial generation wants to learn through immersion training and reverse mentoring
relationships. In this scenario, new employees mentor experienced ones.
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But what’s more important is transforming leadership. Some leaders are stuck in
old school ways of thinking and doing. In an increasingly connected world, they must
become comfortable with the rapid exchange of data and get rid of outdated, hierarchal
structures of operating. Even more importantly, they must engage.
BEST PRACTICE
Lockheed Martin is creating a transformational strategy. “Not an easy task! Not an
email with a newsletter!” They are creating an industry playbook - bringing diverse
experiences together. The challenge is daunting. But it is exciting. For example, how to
bring 100,000 employees along on this journey? It can be achieved by communicating
across all platforms. How do you know when you are on the path to success? Answer:
the adoption rate.
It’s important to recognize that the “digital thread” and inter-office thread facilitate much
easier communication.
Today’s manufacturing environment makes it imperative that leadership no
longer be defined by one single person. Leaders need to collaborate and motivate
within a connected workforce. We cannot rest on what’s been done in the past, we need
to explore the art of the possible, collaborate, and focus on the entire life cycle of
products to enable manufacturing capabilities.
TAKE-AWAY
Leadership has to change in the new era of manufacturing 4.0
The new workforce demands a new model and way of behaving and leadership
must adapt accordingly
KEY INSIGHT
Leadership is no longer about one single leader, it’s about empowering groups to
innovate and lead on their own
FINAL THOUGHT
Manufacturing 4.0 is changing the game of manufacturing. Robotics, virtual reality, and
artificial intelligence all require new ways of looking at the entire business apparatus.
Yet, the most important aspect of making the shift is to understand the changing
workforce. To be an effective business, you’ll need to embrace and adapt to change
and new ways of working.
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______________________________________________________________________
CASE STUDY Cyber in the Age of Digital Manufacturing
PRESENTER
Michele D'Alessandro, Vice President and Chief Information Officer, Manufacturing IT
Merck and Company, Incorporated
Member, Manufacturing Leadership Council Board of Governors
LinkedIn Profile
TIME
Tuesday, June 12, 2018 at 9:10am
______________________________________________________________________
SESSION ABSTRACT
While the Industrial Internet of Things opens up worlds of opportunity, it also opens up
worlds of threat. The integration of cyber and physical, and the hyper connected world
of intelligent devices underpinning Manufacturing 4.0 require that digital security is a top
priority. Are you doing enough to understand and manage your risks?
KEY TAKE-AWAYS
Insight on complexities of the current and evolving threat landscape
Critical factors for Operational Technology (OT) and Industrial Controls
Key learnings and strategies needed
OVERVIEW
The threat of cyber incidents is growing. Global security is a huge responsibility. In
manufacturing, the risk and threat is acute because of the fast pace of transformation
and the technical connectedness.
Agenda
Threat landscape
Critical factors
Lessons learned
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Threat Landscape
Cybersecurity is critical today. Many barometers show that the threat has grown; cyber
thereat is the #1 risk for mid-sized and large companies and the #2 risk for small
companies after supply chain security.
Considerations of cybersecurity risk include:
Data integrity
Regulatory compliance
Risk management controls
Human safety
Confidentiality
Intellectual property
Trade secrets
Business-sensitive information being breached
A specific area of concern for this threat is with industrial control systems as they often
do not use central authentication, nor do they use central change management tools.
Issues might include being maintained in a centralized territory, no antivirus software,
limited logging and auditing capabilities, outdated and obsolete software applications,
and software engines that have limited security knowledge.
Addressing manufacturing technology risk means:
Limiting broad internet access
Using firewalls to control traffic
Implementing strong authentication and access control
Developing a dedicated and secure system/vendor support admin network
Where possible, disabling or filtering USB ports
Consider advanced monitoring solutions tailored to these environments
TAKE-AWAY
Cybersecurity is a leading business threat
Manage the life-cycle of hardware and software equipment
Don’t ignore that you need a life-cycle approach, so that the footprint of aged
assets does not become a risk
Dual vision for the manufacturing plant: Digital plant, resilient plant
Digital means agile manufacturing systems, connectivity, secure info flow, smart
analytics
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KEY INSIGHTS
Case Study
Merck was implicated in an event globally. The need for response was multifaceted.
The organization needed to be prompt, put in recovery efforts, and find out what
happened. Some divisions had good crisis continuity. Others did not, so it was not
consistent across the company. They no longer defer strategies against business
convenience.
Insights derived from Merck experience:
Security profile can only be maintained through deep learning/machine
algorithms
They couldn’t protect any other way
Increased need to protect assets seen as digital, not just physical
Plants need to be online 24/7
Aged asset debt- modernizing our asset debt
Look at the shelf life of all assets
The trick is not to get in that situation. Implement strategies that are as modern as
possible. Take care to look at the shelf life of all assets. For example: Laptops can last
from 6 months to 3 years. After that, they should be replaced.
IMPLEMENTATION GUIDELINES
Strong commitment to a new normal requires:
o Risk management and governance
o Asset management
o Advanced endpoint protection
o Strong security resources
o Segmentation
o Modernization
FINAL THOUGHT
The bottom line is that the transformation to M4.0 is exciting and can be huge for
business. But taking this path does have risks, and it demands better cyber planning
and first-rate execution of the plan.
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______________________________________________________________________
MANUFACTURING LEADERSHIP AWARDS SPOTLIGHT Selected Winners of the 2018 Manufacturing Leadership Awards
PRESENTERS
Various
TIME
Tuesday, June 12, 2018 at 10:10am
______________________________________________________________________
SESSION ABSTRACT
Selected Winners of the 2018 Manufacturing Leadership Awards will give a short
synopsis of their winning projects: what was accomplished for their companies and
lessons learned.
Winner: Bosch
Category: Industrial Internet of Things Leadership
Project: The Factory of the Future
Bosch brought in their first robots In the 90’s, and manual soldering became automated.
Today, their plant in France is a benchmark, with on-time deliveries above 99.5%.
Recent challenges include disruption, and an aging workforce. Supply chains needed to
be shortened, and they needed to diversify and reinvent new technologies to become
innovative and remain competitive. They had to teach their workforce (average age 48)
new skills like scanning.
Outcome: They came up with Manufacturing as a Service, providing a service, repair,
etc. It took some time, but they found new markets, and now they have an engaged
workforce.
Winner: Dow Chemical Company
Category: Operational Excellence Leadership
Project: Unmanned Aerial Vehicle (UAV) and Robotic Platform Initiative
The UAV and Robotics Platform Initiative (Robotics Program) is a new paradigm in
safety; significantly reducing the amount of time personnel are in a potentially
hazardous environment through the use of robotic technology. The Robotics Program
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addressed work that is performed in confined spaces, from elevated surfaces and with
industrial cleaning applications. In addition, Dow was shown as an industry leader in
this space. They were the first in their industry to be granted FAA approval for UAV use
inside their facilities.
Outcome: Dow has an established Robotics Program that is presently using robotic
technology to remove employees from harm’s way. They continue to expand the use of
validated robotic technologies and are setting aggressive targets in safety, such as
eliminating human entry into confined space entries by 2025. Future plans to help
accelerate the development of new robotic applications to meet their needs are to be
accomplished through the expansion of their Robotics Program, the active participation
in industry collaborations and expanding their presence in external industry and
academic partnerships.
Winner: Ford Motor Company
Category: Engineering and Production Technology Leadership
Project: Scalable Powertrain Assembly Lines Enabled by Flexible Robotic Assembly
Technology
Challenge: To go from traditional high volume systems to cost competitive medium and
low volume systems by simultaneously reducing Volume, Investment and Labor by 50
or 75%.
After an initial struggle to find a cost competitive solution the following quote from Henry
Ford really applied: “Failure is simply the opportunity to begin again; this time more
intelligently.” Beginning again, the team employed a “contrarian thought exercise” to
think completely differently about the scalability problem which led to their breakthrough,
a standardized flexible assembly station to do any assembly task.
Result insights: Doing more work in fewer steps is required to be competitive. Automatic
station flexibility is needed to perform multiple work tasks.
Outcome: Ford scaled a High Volume system with 36 stations and 1 task to a Medium
Volume System with 18 stations and 2 tasks to a Low Volume System with 9 stations
and 4 tasks and achieved the required scalability for Volume, Investment and Labor.
Winner: HP Incorporated
Category: Collaborative Innovation Leadership
Project: Open Materials Platform
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Open Materials Platform – instrumental in 3D printing and digital manufacturing.
IBM created the world’s first materials lab. They brought an ecosystem together --
materials scientists and chemists.
HP Open Materials Platform:
They have a number of companies working in their lab
They created branded materials, documented design
Collaboration with healthcare
3D Materials Certification Process:
When a company has a feasible product developed, the HP labs can develop
and pre-commercialize the product
Winner: IBM Corporation
Category: Engineering and Production Technology Leadership Project: Singapore
Advanced Manufacturing Initiative
IBM’s Advanced Manufacturing Technology Initiative encompasses M4.0, machine
learning, augmented reality, system, integration, and IoT. Their journey started with a
vision to be the most smart, efficient, automated company. They looked externally to
determine what the industry and clients needed. They focused on showcasing,
consulting and delivery POC (Proof Of Concept) and solutions like cognitive visual
inspection, Dynamic Supply Chain Dashboard , AR glasses, cognitive AGV, and robot
guided green energy.
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_____________________________________________________________________
CONCURRENT COLLABORATION ZONES – THINK TANKS Zone 1. Manufacturing 4.0: Where do I Begin?
FACILITATOR
David Stonehouse, Global Director of Connected Enterprise, Rockwell Automation
LinkedIn Profile
TIME
Tuesday, June 12, 2018 at 1:50pm
______________________________________________________________________
SESSION ABSTRACT
Expected benefits and returns associated with Manufacturing 4.0 are clear, but the
journey to realize them can be murky. This interactive session outlined the steps
required to successfully orchestrate people, processes and technology across a
transformation roadmap that aligns strategic vision with tangible business outcomes.
KEY TAKE-AWAYS
Insight into finding the value of Manufacturing 4.0 for your business, including a
case history of where Rockwell Automation found value
A framework for aligning business outcome with strategic vision across business,
technology and organization
A step-by step approach to planning your transformation from strategy review
through roadmap
INTRODUCTION
David Stonehouse, the session facilitator, works with companies to determine the value
of digitization. He has been a general and multi-site manager of supply chains. He is a
chemical engineer. He opened the session with an informal poll of participants:
Question: Where is your organization in terms of implementing M4.0? How many are at this stage: “My firm has started, we are early in the M4.0 transition?” Most participants raised their hands
How many are at this stage: “We are just starting out?”
A few participants raised their hands
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David works with people in various stages. His research showed that the following were
the major barriers to getting started with M4.0:
1. Creating a business case
2. Leadership
3. Skills
4. Cyber security
He then delved deeper into how to address these barriers:
1. Business case
Opportunity. What is possible, how can I improve?
Cost - these are new ideas, how much will they cost?
Plan - putting together a plan is hard when you aren’t entirely
knowledgeable
2. Leadership
Interacts with business
Is there a leader? What is their level and function? Supporting team?
Who drives this forward?
3. Skills
Types
Number needed
Have/ rent/consult/contract out for the skills
4. Cyber Security
“Basic computer hygiene” - (i.e. antivirus programs)
Advanced security
Intrusion protection
What do you think should be added to the list? Readiness
Change Management
Resources
Governance
Organization
Education
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Who has put together a successful business case for M4.0? Participant: The business case is very important. We asked questions - intensive
listening [to stakeholders].
We mapped out our value strengths. We looked at constraints and where we had high
labor content and the complexity of the work. We could put a dollar value on the output.
“I’m struggling to understand - What 4.0 is… How can I say I will spend that much money on new technology when I’m already spending money solving these issues?” M4.0 is using different technology to solve problems in new ways. For example, it can
be tracked differently. But the hard part is going through your plant and seeing it in a
new way from the view of M4.0 capability technology, i.e. “The art of the possible”
How do you know how much to spend? Net Present Value (NPV)
Inflows outflows
Outflows - cost
Compliance – justifies the cost
Cost of not doing it
Proof of Value (POV)
Almost like risk management. Will make management a little more open
Minimal viable product
Ask: What am I trying to do? Modernization efforts without a reason are hard to get funded. For example, I go to a
plant and there’s a 30 year old piece of equipment. Since its running, there isn’t a
reason to spend money to fix it. Getting stakeholder involvement is very important
Participant: We have been on the journey for a number of years. We have experienced
good returns, but also unexpected consequences. When it goes wrong, we need to
adapt and change. This has made it successful. And the savings did end up getting
better. There was synergy in having multiple plants do it together.
TAKE-AWAY
From the audience’s response, business case was a leading barrier to
implementing M4.0
M4.0 isn’t about technology for technology’s sake. It’s about key issues, labor,
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list of high value targets that tech can solve, so it’s in line with the business
KEY INSIGHTS
The business case of M4.0 needs to be cross functional
Stakeholder involvement and feedback are necessary
Some of the M4.0 initiatives will make new sales and tap new revenue streams
The groups who are most successful at M4.0 have a budget and resources for it;
it is planned
FINAL THOUGHT
The many factors that go into M4.0 require a cross-functional approach to outline its
uses and long-term planning profitability. It’s not just modernization for the sake of
updating; it will require multiple stakeholder involvement and openness to change and
re-thinking operations and strategy.
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____________________________________________________________________
CONCURRENT COLLABORATION ZONES – THINK TANKS Zone 2. Applying Artificial Intelligence and Machine Learning for Competitive Advantage
FACILITATOR
Doug Reeder, Innovation Leader, Office of the CTO, NTT DATA
LinkedIn Profile
TIME
Tuesday, June 12, 2018 at 1:50pm
______________________________________________________________________
SESSION ABSTRACT
Artificial intelligence (AI) is gaining prevalence in manufacturing as the technologies
advance, data management and algorithms improve, and as organizations discover how
AI can be applied to solve some of their most challenging issues. Participants in this
informative and interactive discussion learned how AI is being used in manufacturing to
improve production yields, reduce waste, optimize supply chains and gain predictive
insights that deliver more value and provide a competitive advantage.
KEY TAKE-AWAYS
Examples of where AI is being applied in manufacturing
Considerations for planning your AI strategy
Perspectives on identifying areas where AI can help you gain competitive
advantage
INTRODUCTION
An informal assessment at the start of this session reflected that most participants had a
basic, but not advanced understanding of AI. Most were starting to use AI, though few
had an AI or Machine Learning (ML) roadmap.
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Artificial Intelligence (AI) and Machine Learning (ML) Definitions:
TAKE AWAY
Systems of Record and Systems of Engagement now enable Systems of Insight
through the application of AI and ML, which enables innovation:
o Systems of Record – Historically the focus of information and operational
technology organizations, included systems that recorded operational logs,
performance, time-series data, production output, inventory, financial
accounting, customer interactions, sales, human resource, and other data
o Systems of Engagement – Evolutionary from Systems of Record, systems
facilitated by the internet, wireless technologies, sensor systems and social
media that produce vast amounts of data from interactions, collaborations,
dialogs, videos, texts, tweets, and blogs. This shift began with commercial
use of the internet in the mid-1990s and accelerated with the broad adoption
of social media (Facebook, Twitter, etc.) and mobility
o Systems of Insight – Historically, statistical analysis and data mining, now
enabled by Artificial Intelligence systems, enabled organizations to derive
more meaningful insights from historical and real-time data from Systems of
Record and Systems of Engagement data to achieve their objectives and
mission. Today’s machine learning and deep learning technologies are
providing better insights than ever before
o Systems of Innovation – Using actionable insights from Systems of Insights,
the promises of innovating from “Big Data” analysis are being realized.
Organizations can incrementally innovate through new operational controls,
advanced automation that reduce cycle times, dramatically improve quality
and increased first-pass yield and do completely new things including
development of new disruptive business models.
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DEEP LEARNING DEFINITION
Deep learning refers to the use of artificial neural networks with many layers to perform
complex functions with massive amounts of data. Each layer transforms the data into
something more abstract. The final output layer then combines all those features to
make a prediction.
MACHINE LEARNING DEFINITION
Machine Learning – Gives “computers the ability to learn without being explicitly
programmed” (Arthur Samuel, 1959)
Machine learning (ML) is a type of artificial intelligence in which a machine is trained to
learn from past experiences and make decisions when exposed to new information
without being explicitly programmed to do so. A software program learns from input-
output examples and recognizes trends in the data. When presented with new data, it
makes a prediction based on past examples. Machine learning tasks can be classified
in several categories. The primary types of machine learning are:
Supervised learning
Unsupervised learning
Reinforcement learning
o Supervised Machine Learning - With supervised machine learning, the
program is trained on a set of examples (training dataset) in which we already
know what the desired output should be based on the input. (Think of it like a
set of questions and answers.) Following this logic, the program can make an
accurate decision when given new data. Essentially, we label or classify the
data and teach the machine the patterns in the data, than the machine
applies those learning to new data to make decisions.
o Unsupervised Machine Learning - In unsupervised learning, the program
must find hidden patterns and relationships in the data without any guidance.
The machine teaches itself by finding patterns, making mistakes, and self-
correcting
o Reinforcement Learning - With reinforcement learning, a machine learns by
trial and error and the consequences of its actions. If the machine gets the
right answer, it gets a reward. If it gets the wrong answer, it gets a
punishment. In this way, we teach the machine to act in a specific way to
maximize its performance
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APPLIED ANALYTICS
Descriptive Analytics: Provide hindsight. Tells you what happened from
historical data with reporting, scorecards, clustering etc.
Diagnostic Analytics: Provides insight. Tells you why it happened from
historical data
Predictive Analytics: Provides foresight, what may occur. Analysis of current
and historical data to detect potential risks, identify opportunities and make
predictions about behaviors and future or otherwise unknown events
Prescriptive Analytics: Provides optimal recommendations using optimization,
simulation, etc. for decision making. Unlike predictive analytics, prescriptive
analytics seeks to determine ways in which processes or operational conditions
should be modified. Answers the question, “What should we do about it?”
SAMPLE MACHINE LEARNING FUNCTIONS
Numerical – Pattern discovery, rankings, correlations, associations
Image Recognition - Classification of images
Image Detection - Locate and classify objects in images
Speech Recognition - Convert speech to text
Text-to-Speech – Convert text to speech
Natural Language Processing (NLP) – Extract context and meaning from text
Generative Models - generating objects that can be rendered digitally (graphics,
photos, audio, text, code, and even manufactured items)
Examples of where AI is being applied in manufacturing:
1. Quality
A. Higher First-Pass Yield with ML
i. Improving semiconductor manufacturing yields up to 30%
B. Increased efficiency with ML
i. Reducing scrap rates
ii. Optimizing fab operations is achievable
C. Automating quality testing using ML
D. Increasing defect detection rates up to 90%
E. Increased predictability of production outcomes – in some manufacturing
processes, particularly in processes manufacturing, unpredictable outcomes
of complex and specialized processes can be better understood.
F. Increasing production yield and scalability – selecting the best possible staff,
suppliers, and machines
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2. Speed
A. Increased efficiency with ML
i. Optimizing JIT manufacturing by reducing supply chain forecasting errors
by 50% - resulting in fewer lost sales by 65% with better product
availability is achievable
ii. Improve Maintenance, Repair and Operating supply (MRO) Spare
optimization (and obsolescence costs)
iii. Increase production yield and scalability – selecting the best possible staff,
suppliers, and machines
APPLICATIONS IN MANUFACTURING
Predictive Maintenance
o Cylinder replacements
o AT&T’s example: AI for network and U-verse service on the residential
gateways. Monitoring the service to ensure business continuity. Looks at
worldwide traffic patterns for cyber security and predicting network
performance. Saves the company money
o NTT sound anomaly detection
Listen to normal
React to what’s not normal
o Power supply company – listens to sound on the power grid. Listens for
anomalies to predict outages, failures and react
Supply Chain
o Supply Chain Risk Assessment –Where you map supply chain
tendencies, look at weather, listen, look at social media, then assess risk
for the entire supply chain
o Disaster Recovery –Short term demand analysis
o Discussion of use of social listening as an input to decision making and
understanding product defects
o Some companies use data to understand how to work with regulators
o IBM – Using 6 years of data. Very complex model. Demand sensing with
lots of historical data
Machine Learning
o Seasonality and event driven demand
o http://tylervigen.com and his “spurious-correlations”
o Machine learning concerns
o Erroneous causality
o Bias
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o Be careful with the data – validation and re-validation. There are lots of
best practices available
o Possible pitfall - If bias shows up and harms someone who is responsible
Input from audience member (SAS) – running ML on top of neural network
to explain why the machine is interpreting what it is. The challenge is the
output
o Supply efficiency (reducing waste aka: waste management)
Who owns AI/ML? Is it “just another IT project”? If you think so, you will fail
miserably
KEY INSIGHTS Three perspectives on identifying areas where AI can help you gain competitive
advantage.
1. Be realistic – Amara's Law states that “We tend to overestimate the effect of a
technology in the short run and underestimate the effect in the long run.” AI is a
set of tools that can help, but exercise caution on expectations
2. AI is getting good at classifying things, tagging pictures, identifying normal and
anomalies
3. Set up your hypothesis – Be specific. Look to solve a well-defined problem(s)
IMPLEMENTATION GUIDELINES
Five considerations for planning your AI strategy:
1. Understand that AI products are data products
2. Training AI requires data – lots of data. Data that has been prepared. Metadata
additions, error correction, deduplication, filtering, categorization, classification
3. Be data literate – have data to train AI
4. Look at your strengths – Where do you have data that can be used to reveal
hidden patterns to gain insights?
5. Identify critical areas that require consistent precision and continual performance
BEST PRACTICE
Consider employing data scientist(s) – they are critical to this process. There are
generally three separate roles:
Data engineer to organize the data
Data scientist who investigates the data
Software engineer who implements the applications
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This will change in the coming years as AI tools become simpler to use and the “Citizen
Scientist” community rises, putting powerful AI tools into the hands of average workers
who work with and can prepare data to gain insights.
FINAL THOUGHT
More data = Better results
Data: Validate. Revalidate. Cleanse
Start with a well-defined problem statement
Start small. Be realistic
It’s not an IT project. Context is EVERYTHING
Understand who owns the data. Where it’s coming from
Train on the cloud. Execute on the edge
Learning curves matter
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_____________________________________________________________________
CONCURRENT COLLABORATION ZONES – THINK TANKS Zone 3. Building Your Digital Enterprise
FACILITATOR
Tom Tengan, Director Digital Enterprise, Siemens PLM
LinkedIn Profile
TIME
Tuesday, June 12, 2018 at 1:50pm
______________________________________________________________________
SESSION ABSTRACT
Do you have a digital strategy for your enterprise? Digitalization is changing our daily
lives as well as transforming existing business models from product-centric
development and manufacturing to creating opportunities for extended value throughout
the lifecycle. This increases pressure on product development but opens up new
business opportunities at the same time. Successful companies are seizing the
opportunities offered by digitalization to increase their competitiveness in the digital
world. According to C-Suite execs, digital disruption will wipe out 40 percent of Fortune
500 firms in the next 10 years.
KEY TAKE-AWAYS
A better understanding of the technology trends transforming industry and
shaping the Digital Enterprise
An understanding of the key components that comprise a digital enterprise
A guide to develop a framework for your own digital innovation strategy
OVERVIEW
This break-out session underscored that in the M4.0 era nothing is off limits. You can
use data for everything, including having golf clubs collect information about your swing.
It’s that comprehensive. Digitalization, trends in digitalization, implications, possibilities,
and solutions were all examined.
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Trends
The most glaring trend is that transformation is happening everywhere. And with it,
speed, flexibility, quality and efficiency are getting better. This has produced a new
business model with speed or time to market highly important. Flexibility must come into
play because people demand combinations of products. For instance, Adidas has a
store where you can go and customize your shoe and walk out of the store with that
shoe.
Other trends include efficiency or how green your business is. Cyber security is also a
huge trend as well as quality.
Implications
Beyond trends, the group looked at implications which encompass the three big
domains of manufacturing:
1. Ideation or development
2. Realization - how do you make the product
3. Utilization - what happens when the product goes out the door
Five value streams of manufacturing
1. Product design
2. Production
3. Planning
4. Engineering
5. Execution and servicing
Today’s industry trends are putting great strain on the manufacturing stream or chain.
For instance, it’s now necessary to look at software to supply solutions. It’s safe to say
that people who are going to be leaders in vertical in the future are in software.
When we think about trends and implications, we start to think about possibilities: The
digital revolution, data driven manufacturing and revolutionizing production and the
manufacturing process with data.
Virtual testing
Going forward, you’ll want to virtually verify and test, with an expectation of shortening
the time to market. By verifying and testing virtually, the only cost is time. You can gain
foresight from the virtual world into how products will be used and in the process, you
can learn new uses for products.
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The struggle with M4.0 is getting past well-established processes. The key is to start
small but think big. Nobody wants to change an existing, large scale system. You need
a collaboration platform. Information has to flow from one value stream to another.
Challenges
But challenges remain… organizational issues such as leaders not wanting to upset the
status quo and change processes. There is also the issue of the overwhelming amount
of data available. It’s hard to define a big picture approach in the face of it, let alone
scale it. But the key is to look for an opportunity to deploy new technology as separate
from the rest of the company, see how it works and go from there, i.e., apply it on a
larger scale.
FINAL THOUGHT
Start small but think big.
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_____________________________________________________________________
CONCURRENT COLLABORATION ZONES – THINK TANKS Zone 4. A Manufacturing 4.0 Roadmap for Legacy Assets
FACILITATOR
David Meek, Partner, IBM
LinkedIn Profile
TIME
Tuesday, June 12, 2018 at 1:50pm
______________________________________________________________________
SESSION ABSTRACT
Legacy equipment is one of the biggest obstacles to Industry 4.0 adoption.
Manufacturers struggle with a scalable and cost-effective way to connect them to a
single platform and collect information from them. In this interactive session, Meek
provided a digitization roadmap that will take you from silos of information to an
integrated, smart factory. Participants also learned how to prioritize projects to achieve
less downtime, increase productivity, and lower costs
KEY TAKE-AWAYS
Key success factors for adopting Industry 4.0 with legacy equipment
Best practices to prioritize projects
Sample digitization roadmap for your legacy equipment
INTRODUCTION
Background of speaker David Meek:
Engineer by training
27 years deploying systems to manufacturing floors and supply chains
Spent the last 3-4 years adding artificial intelligence to the shop floor to improve
throughput and efficiency for plants
What people wanted to learn about, based on survey results prior to the session:
Vision/Roadmap/Plan – 11
Business and use cases – 7
Data and information – 3
Connectivity – 5
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Top challenges from participants (on site):
How to prioritize assets - Do I use sensors for everything?
Long term maintainability - Program versus specific
Pitfalls - Legacy assets and instrumentation
What does M4.0 mean for a legacy asset versus a new asset? Is there a
minimum level?
TAKE-AWAY
Start with the use case, not the data
Go where the biggest cost is
Find a quick win
Have a plan to deploy in similar processes across the business
KEY QUESTIONS
Most manufacturers are asking IBM:
How do we hook up, automate and sensor our old assets? (The cost to update
equipment is exorbitant)
Start with the value and the use case. You don’t need to sensor everything. Less than
1% of all data is useful. Also, don’t overlook replacing or upgrading legacy assets
through the original equipment manufacturer, or OEM. Many OEMs have
update/upgrade programs to swap out your legacy assets with new, instrumented
equipment.
Should I wire everything or deploy wireless to the shop floor? It depends on the application but the trend is more and more companies are deploying
wireless to the shop floor to support IoT and mobile applications Examples of
companies bringing wireless to the shop floor include Cisco, Intel and AT&T.
Is there a cheat sheet of what sensors to put on what? No – it’s use case and equipment specific. Due to the rapid pace that sensors are
improving at, the new capabilities that are being added to old sensors, and the
decreasing cost of custom sensors, it’s impossible to create a one size fits all cheat
sheet .
How much should I spend per project? Average cost for a pilot should be in the $150k to $400k range. If you spend less,
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you’re not going to see the value. If you’re spending more, you’re scope is too big -
scale back.
How long should it take to see results? It depends on the size of the company and the capital available. Average time is 3
months to 2 years. Most want payback within the year. Most projects show value after
the 3 month pilot, further deployment is needed to realize the full value.
IMPLEMENTATION GUIDELINES
1. Start with a use case
2. Once you have your use case, you can identify the data, the assets, and the
components of the process you need to focus on
3. Build the business case, what is the dollar value you expect to get?
4. Invest in an IoT platform
o Downside of an IoT platform: you’ll need to train your staff, you’re bringing
new technology into the ecosystem
o Upside of an IoT platform: They are good at managing devices, and pushing
analytics down to the edge devices. It’s easy to build logic so only relevant
information is sent to the cloud.
o Security: You can shut it down if someone is trying to connect to it. You can
connect new APIs as well – example Watson APIs
Use case areas:
Assets – Leverage data from assets to maximize uptime
Production – Optimize processes/avoid quality issues before they happen
Inventory/working capital – Focus here when there is a high value asset
Logistics/supply chain – Seeing a lot of examples here from consumer goods
space, new consortiums being formed around Blockchain
Customer interaction/consumerization – Monetize your data and create new
streams of revenue
BEST PRACTICE
Don’t start with data
A lot of companies spend years fixing all the data
Taking a use case approach is much more pragmatic
Less than 1% of the data is useful
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Don’t just focus on the big stoppages
It’s better to focus on repetitive stoppages that add up over time – they end up
being more than the biggest stoppages
Best practices for prioritizing projects:
Focus on the value – such as increasing throughput/quality, that will dictate the
sensors you need
If you have old and new assets in same asset class, start with new assets first
o Example: We helped a client optimize a steel blast furnace that creates
4500 data elements every 100 milliseconds, but determined they only
needed to collect 125 data points every 15 minutes to optimize that
process
Use soft sensors to predict reading. People will try to sell you sensors that are
either not necessary, or not optimized for the environment. Often, sensors can be
interpolated using analytics to get the values needed
Best practice for building a business case:
Look at more than one option – compare connectivity needs, level of effort, and ease
of sharing across the business
Biggest pitfalls from human side:
Starting an IoT project in IT. We (IBM) have seen IoT projects die because they
started and ended in IT
Never engaging the plant manager. We (IBM) have seen projects championed
by management fail because they did not involve the plant manager from the
beginning
Focusing on the worst performing plant. We (IBM) have seen better success
focusing on the plant with a plant manager who will champion the project
Best practices for human side of M4.0:
Create new competencies and skills (Data science is one)
Get backing of overall roadmap from corporate
Look for plant with plant manager that champions M4.0 – rather than the worst
performing plant
Get feedback from operators – untapped natural resource
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Best practice for implementation:
Start small –Don’t do everything, start with one, learn a lot, prove to management
Have a plan - lots of companies are doing things piecemeal and/or have pockets
of self-education. The sweet spot for M4.0 is in the OT department
Pilot should be production ready after completion
Deploy to same process in other plants or to similar processes in the same plant
ACTION ITEM
Recommendation for the Manufacturing Leadership Council: Build a capability maturity
index comparison for members
FINAL THOUGHT
It bears repeating: Don’t start with the data - start with the use case!
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_____________________________________________________________________
CONCURRENT COLLABORATION ZONES – THINK TANKS Zone 5. Using the IoT to Elevate Supply Chain Visibility
CO-FACILITATORS
James Hilton, Director, Vertical Marketing Strategy, Manufacturing, Zebra Technologies
LinkedIn Profile
Mark Wheeler, Director, Supply Chain Solutions, Zebra Technologies
LinkedIn Profile
TIME
Tuesday, June 12, 2018 at 1:50pm
______________________________________________________________________
SESSION ABSTRACT
Technology can provide unprecedented visibility to the location and state of goods,
assets and people throughout the manufacturing enterprise. While legacy systems of
record and even control systems may not be poised to leverage this data, this visibility
is increasingly both achievable and affordable. What could you accomplish with
complete visibility to goods, assets and people? Could you improve plant or line
utilization? Improve quality? Gain the insights needed for continuous improvement?
Improve safety? Improve your ability to adapt and respond to the unplanned and
unforeseen?
KEY TAKE-AWAYS
An understanding of how IoT technologies can significantly boost visibility
Insights from real-life case studies on ROI
Examples of how an agile project approach can ascertain feasibility and benefits
quickly
Participants offered these use cases or IoT applications:
Rack tracking for providing customer RTL of orders
RFID for Personnel Tracking
Frictionless Transactions - manual scanning reduction
Digital Performance management
Warehouse Movement
Goods in Route
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KEY INSIGHTS
1. The concept of where to provide IoT in the supply chain is confusing to many
A. Many participants were interested in determining the best place to start
with IoT implantation as well as achieving a short term ROI
i. Solutions that can be tied to safety initiatives are easier to sell to
management
ii. Solutions that can be used for safety initiatives and supply chain
functions provide value to management
iii. Solutions that provide next best action are also desirable
iv. Line replenishment
v. Worker Proximity
B. Participants seemed to focus on specific technologies versus identifying
the problem and quantifying ROI if the problem is resolved. This is an
industry trend, not specific to the group
2. Consensus of the participants was that the adoption of IoT will force an IT and
OT convergence
A. One participant noted that they use the Continuous Improvement group as
the connection between the two groups
3. Advancement in mechanization in the supply chain
A. Over half of the participants are using more mechanization in their supply
chain now.
i. AGVs were being used in some capacity by 60% of the room. This
technology is being deployed in lieu of Tugs
ii. Drone technology was being used by one attendee for inspections
BEST PRACTICE
Questions asked related to best practices:
1. One participant asked about technologies available to track metal stock,
specifically using passive RFID
A. Zebra provides a SilverLine solution that is designed to be applied and
read by UHF readers on metal substrates
2. How can tracking the location move beyond the four-wall supply chain?
A. Discussions around having 3PL’s tag and read customer inventory at their
sites, prior to shipping (advanced notice)
i. Pallets and Returnable Totes
3. Are their solutions available to make the reading of labels coming from suppliers
more consistent and faster to receive?
A. Standards like GS1 are available that make label information “standard”
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B. If the data on the label adheres to these standards, it can be parsed out
quickly to improve a number of processes (speed and accuracy)
C. One participant reinforced the fact that you need to mandate that your
suppliers adhere to whatever standard you designate. Most suppliers will
not go the extra mile if not made to
FINAL THOUGHT
Collectively, the Think Tank participants agreed with the moderators that actionable
visibility is critical across the operation. Supporting findings below come from a Zebra
Vision Study:
Manufacturers will continue to adopt Industry 4.0 and the smart factory, in
which workers use a combination of radio frequency identification (RFID),
wearables, automated systems and other emerging technologies to monitor the
physical processes of the plant and enable companies to make decentralized
decisions. By 2022, 64 percent of manufacturers expect to be fully connected
(sharing data across production, supply chain and workers) compared to just 43
percent today
Manual processes are expected to dramatically decline. Today, 62 percent of
those surveyed use pen and paper to track vital manufacturing steps and this is
expected to drop to only one in five by 2022. The use of pen and paper to track
work in progress (WIP) is highly inefficient and makes the process susceptible to
human error
Executives across all regions cited achieving quality assurance as their top
priority over the next five years. Forward-looking manufacturers are embracing
a quality-minded philosophy to drive growth and profitability By 2021. Only 34
percent expect to rate this as a top concern – signaling that improvements made
by both suppliers and manufacturers will ultimately improve the quality of finished
goods
Fifty-one percent of companies are planning to expand the use of voice
technology in the next five years. The most dramatic growth for voice
technology will be in the largest companies (>$1 Billion) with a reported use
growing to 55 percent by 2022
One-half of manufacturers plan to adopt wearable technologies by 2022 and
55 percent of current wearable users expect to expand their level of usage in the
next five years
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_____________________________________________________________________
CASE STUDY Embarking on the Manufacturing 4.0 Journey
PRESENTER
Praveen Jonnala, Vice President, Global Business Solutions, CommScope
Member, Manufacturing Leadership Council
LinkedIn Profile
TIME
Tuesday, June 12, 2018 at 1:50pm
______________________________________________________________________
SESSION ABSTRACT
Manufacturing 4.0 is not just about manufacturing. It is a key capability to enhance
Customer Experience. Embarking on Manufacturing 4.0 is not a discrete process just to
focus on automating factories and supply chain, it is a continuous journey to enhance
customer experience and deliver compelling capabilities to drive customer obsession.
This session focused on how to start the journey, foundational aspects of the roadmap,
and ultimately how to make it an integral part of your digital customer experience.
KEY TAKE-AWAYS
Insight on how to approach the M4.0 journey, developing a roadmap and
prioritizing the execution based on customer expectations
An understanding why technology is not a magic button and but a key enabler to
accelerate the execution and enhance the value
Key success factors – Enterprise wide engagement, process simplification and a
GREAT TEAM!!
INTRODUCTION
CommScope is in the process of transforming digital communication. They’re also in the
middle of Manufacturing 4.0 which to them consists of 3D-printing, automation,
manufacturing execution systems (MES) and IoT. It’s a new world order of disrupters
and enablers. But, like all businesses, for them it’s about the customer.
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TAKE AWAY
In order to build a strategy around the customer experience, CommScope needed to
forge a new vision. This new vision was built around concepts like agility, data,
simplification and being customer-led. To accomplish this, they would be mindful of AI,
the need for good data, and the fact that speed is a minimum requirement for
customers.
CommScope also needed to implement a factory functional framework. This would
include ideas related to customer experience and agility. It also incorporated
foundational initiatives like Enterprise Resource Planning and simplifying data
governance. They also put in place a Road Map Execution Priority list dedicated to
improving the customer experience and driving innovation and growth.
CommScope key beliefs:
Customer experience is the goal; every business requires it!
Customer is focus, if you do not provide the BEST customer experience, you
won’t stay in business
Everything they do is for the customer
Customer obsession - customer led, simplify, data, agility
Build the customer experience or journey, then make Manufacturing 4.0
the 4th pillar
Factory functional framework:
Identify top 3-5 impacts to customer
Take a look at failure rates, look at the journey, vision systems
Look to the future. For example, robots and 3D printing
How could they use their training cycle but make it more effective?
Change management:
Not about ROI. No- it is about keeping your customers
Tips for change management:
o Challenge the status quo
o Develop urgency to create business
o Ask why and what is in it for your customers
Lessons learned
Focus on value creation, not on technology and automation
Customer focus versus internal improvements
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There is no easy button. Invest in the core foundation including IT infrastructure,
data, core processes etc.
Manufacturing 4.0 is not about just manufacturing! It is about enterprise-wide
engagement
Do not just look at it as a single silo
CommScope realized the need to strive for a balance between customer focus and
internal improvements. They learned to simplify, offer continuous delivery, build the
momentum, build a great team and collaborate and collaborate.
KEY INSIGHT
Collaboration is the name of the game, and you can’t lose making the customer
the centerpiece of your business strategy
FINAL THOUGHT
For CommScope, it’s all about collaboration and customer engagement. Their notions
on Manufacturing 4.0 are built out from that centerpiece.
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_____________________________________________________________________
EXECUTIVE INSIGHTS An SMB’s M4.0 Cultural Transformation
PRESENTER
Daniel Dwight, President and Chief Executive Officer, Cooley Group
Member, Manufacturing Leadership Council
LinkedIn Profile
TIME
Tuesday, June 12, 2018 at 3:55pm
______________________________________________________________________
View video here: https://vimeo.com/frostsullivan/review/273734760/10c377d55b
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SESSION ABSTRACT
Achieving Sustainable Growth at Cooley has required a cultural transformation.
Motivated to transform from being a 90-year-old asset-oriented manufacturer to a
people and process-oriented, highly diversified solutions provider, Cooley is
successfully driving sustainable growth, using M4.0 as a rallying cry. They are part way
to the M4.0 summit, but the air is getting thinner and the climbing more technically
difficult.
KEY TAKE-AWAYS
Insight on implementing collaboration as a business culture and an
understanding of the critical role it plays in company growth
Best practices for developing strategies to get the right people in the right
positions managing the right processes collaborating with the right partners
Key findings for why manufacturing capacity and product performance are the
most relevant KPIs
Examples of why highly flexible mass production is the new operating norm
OVERVIEW
The session opened with an isolated, imposing image of K2. The daunting prospect of
summiting the mountain’s peak is a recurring metaphor throughout Dan Dwight’s
presentation. The mountain represents the overwhelming prospect of revolutionizing the
90-year-old textile company, Cooley Group, in the dawn of M4.0. But, like any good
Arctic explorer, Dan Dwight, Cooley President and Chief Executive Officer, had a plan
and a vision to get to the top of the mountain.
Cooley Group designs and manufactures high-performance, flexible geomembranes
used worldwide for diverse applications including environmental liners; water, fuel, and
chemical containment; billboards and more.
Lessons in Leadership: Summiting K2 and M4.0
There were numerous attempts to summit K2, but most resulted in injuries,
fatalities and disappointment. It wasn’t until climbers recognized the mutual
importance of vision, execution and collaboration that a team finally reached the
summit of K2
Lesson to apply: You need a collaborative team with common priorities to
successfully summit Manufacturing 4.0
Cooley Group applied the same principles as successful mountaineers as they
transformed their organization to meet modern business demands
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Why Cooley Group is pursuing M4.0:
Sustainable Growth Model: Think beyond “economic prosperity” and appreciate
what it means to be truly “environmentally sustainable” and “socially responsible.”
Consider the positive impacts these goals have on your business overall
Rethinking the Approach: Transition production from being asset-driven to
service-oriented
Reinforce the Right Objective: Sell solutions not products to better meet your
customers’ needs in the market
Customize Solutions: Establish reputation for customization while operating
under conditions of mass production
Cooley Group set the following execution objectives:
M4.0 isn’t an end-goal; it’s a necessary process tool if you have any hope of
achieving sustainable growth in 2018 and beyond
Reinforce collaboration as a non-negotiable in the workplace
Regardless of our implementation of the latest technology, the ongoing
collaboration of people, processes and partners is foundational to Cooley’s
business success
Embrace Cognitive Manufacturing: Gather data that can predict when a machine
component is going to fail. Use the information to proactively replace the
component before it fails
Implement hardware for M4.0 that incorporates safety, energy independence,
automation and predictive maintenance
Results of Manufacturing 4.0:
Product performance: Customer product returns were 2.0% in 2014. By 2017,
customer returns are less than 0.1%
Production capacity: Production capacity was 87,000 yards in 2014. By 2018
capacity had increased to 250,000 yards
Additional examples of M4.0 changes:
o In 2014, if a motor went down, the system went down for five weeks. Since
Cooley’s implementation of cognitive manufacturing, when a motor goes
down in 2018, the system is up again the same day
o Cooley utilizes autonomous self-correction to conduct quality control
electronically rather than manually
TAKE-AWAYS
Company culture begins, thrives, or dies with leadership
Collaboration at Cooley is non-negotiable:
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o Collaboration is more than a corporate buzzword. Engage directly with
partners, open-up feedback loops across corporate hierarchies, and establish
Cross Functional Projects (CFPs) to get everyone at all levels and functions
of the business working together to solve material business problems
Cooley Group completely transformed the company to achieve a record-high
revenue increase by embracing collaboration, cognitive manufacturing and the
latest technologies provided by Manufacturing 4.0
FINAL THOUGHT
To be effective in the Manufacturing 4.0 era is to understand how to collaborate as a
team. No mountain will be scaled without teamwork, whether the teamwork is person to
person or man to machine.
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_____________________________________________________________________
KEYNOTE Leadership in the Digital Age
PRESENTER
Stephen Engel, Senior Vice President, Strategic Solutions Leader, Americas,
Hitachi Consulting
LinkedIn Profile
TIME
Tuesday, June 12, 2018 at 4:25pm
______________________________________________________________________
View video here: https://vimeo.com/frostsullivan/review/277494736/6e4b143d3d
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SESSION ABSTRACT
What is the profile of a manufacturing leader in the digital age? Participants learned
about the behaviors, skills, and acumen a leader needs to enable their company to
successfully embrace Digital Manufacturing. No matter where you are on the journey of
digital transformation – these six steps can help you lead in the digital age and connect
your systems to drive new levels of productivity, profitability and value across your
business.
KEY TAKE-AWAYS
Insight on how to connect your physical and digital value streams to drive
innovation
Key steps to identify areas of variation across the physical value stream that can
be supported by better data and real-time analytics
Key findings for why manufacturing capacity and product performance are the
most relevant KPIs
Examples of why highly flexible mass production is the new operating norm
OVERVIEW
Let’s talk about how leadership can embrace M4.0. Digital is evolving you to move:
From selling products to outcomes
From batch to real time
From reactive to predictive
From on premise to cloud
From closed to open source
From individual optimization to overall optimization
What’s your strategy? Where’s your roadmap? How do you talk to your teams? Most
companies don’t have an answer. Digital should be seen less as a thing and more as a
way of doing things.
Digital “laggards” versus digital leaders:
Digital leaders make smarter IT investments
Digital Supply chain and manufacturing journey:
Leverage Iot. Whether you are starting the journey or further along, ask: Can I
see my data, and analyze it?
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Journey to digital transformation:
Six steps for success in every project
1. Set clear goals
2. Identify areas of variation
3. Select point of view use cases
4. Create an Executive Advisory Board
5. Focus on Results
6. Seek advice from the outside
Digital Leaders focus on results and behavior change. They:
Improve the process
Align the organization
Enable technology
Track performance
Communicate
About Hitachi:
The company has been around for 100 years. They’ve accumulated Operational
Technology for 107 years and IT for 58 years. Improvement is in the DNA of the
company. After all, they have the highest number of patents in the world. For them the
key to accelerate digital transformation resides in 5 factors:
1. Remove the lenses you have used to view your role – be a strategic enabler
2. Follow up on a relationship you started here in another industry
3. Set priorities based on business need not technology readiness
4. Embrace for radical change
5. Engage the C suite at a richer level
These tenets will start you on your journey to digital transformation. But you’ve got to
engage with other leaders. You also need to connect with other industries, go to new
plants, and mix it up.
Align yourselves with partners who can supply what you lack. This is helpful in getting
on the digital fast track. Remember too that digital leaders focus on results and behavior
change. This means improving processes, aligning the organization, enabling
technology, and tracking performance. For most companies, the number one failure is
communication.
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Ask: How do we connect physical and digital value streams? And how do we go from
physical value to digital value stream to new unlocked value stream?
TAKE-AWAY
Don’t think in antiquated ways as it relates to your role, be a strategic enabler. It’s very
important to foster relationships to people in other industries. Somewhere there may be
the solution to a problem you have. It’s key to establish a path based on a business
need, not a technology you possess.
FINAL THOUGHT
Embrace for radical change, it is coming whether you like it or not.
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______________________________________________________________________
PANEL DISCUSSION
SMB Perspectives on Manufacturing 4.0
MODERATOR
David R. Brousell, Co-Founder, Manufacturing Leadership Council
LinkedIn Profile
PANELISTS INCLUDE
Daniel Dwight, President and Chief Executive Officer, Cooley Group Member,
Manufacturing Leadership Council
LinkedIn Profile
Vicki Holt, President and Chief Executive Officer, Proto Labs, Incorporated,
Member, Manufacturing Leadership Council Board of Governors
LinkedIn Profile
Ryan Lanham, Information Technology Manager, Dynomax Incorporated
LinkedIn Profile
Richard Sade, Vice President and Chief Operating Officer, S&S Hinge
Member, Manufacturing Leadership Council Board of Governors
LinkedIn Profile
TIME
Tuesday, June 12, 2018 at 4:55pm
______________________________________________________________________
SESSION ABSTRACT
Manufacturing 4.0 isn’t just for large, multi-billion dollar companies. Small- and medium-
size manufacturing companies have the opportunity to level the playing field by adopting
advanced IT and automation technologies. Nevertheless, SMB companies do face an
array of unique M4.0-related challenges in technology evaluation, financial wherewithal,
and business model transformation.
KEY TAKE-AWAYS
Examples of how SMB manufacturers assess the M4.0 opportunity
Insight on the technology priorities for SMB manufacturers
Key factors for how SMB companies deal with value chain requirements
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OVERVIEW
96 to 97% of manufacturing companies in the U.S. are small and medium sized
businesses, also, also known as SMBs. Is there a digital divide between small and large
companies seeking to implement Manufacturing 4.0? Is M 4.0 just for big companies?
Or is it “all aboard” for the 4th industrial revolution? David Brousell sought answers to
these questions and others with a quartet of diverse SMB panelists.
Question: Do you – representing SMB companies – feel you have the same opportunities as larger companies in implementing and leveraging M4.0? As our company (Proto Labs) accelerates innovation and creates prototypes, we have
always had an eye on automating processes for manufacturing. Regarding the M4.0
journey, smaller companies can have an advantage as there are smaller groups of
employees that you can more easily engage personally and “wrap your arms around.”
It’s easier to create a cultural change in a smaller organization and you can usually do it
much more quickly.
Disadvantages in smaller companies can include resource and skill set challenges as
there may be less of them. Smaller organizations may need to connect with larger
ecosystems; events like these are helpful as they foster idea sharing and access to
talent, too.
As a small manufacturing company with automated processes, one disadvantage is
limited resources from a financial standpoint. But an advantage is there is no corporate
hierarchy, just a partnership. We have also learned to partner with other companies for
talent and resources and to connect with a larger ecosystem. We work at sustaining
long range thinking. Overall, we recognize that there are two main aspects to M4.0: the
“hard” meaning machines and technology and the “soft” meaning the people. You need
to address both.
A participant from an industrial solutions manufacturer stated that they began leveraging
M4.0 about a year ago to improve communications and productivity on the shop floor,
and to enhance business overall. He described the process as akin to taking IT right to
the C-Suite.
Another manufacturing leader explained that the three different divisions of his company
had very different competitors, including a huge conglomerate with lots of resources,
other SMBs trying to move ahead and China.
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As more and more companies embrace M4.0, is it going to be harder to find a competitive advantage? Participant: we have already created a competitive advantage; it’s a selling point. This
has created a situation where other companies seek out doing business with us. It also
shows their common customer base that other companies are not (yet) doing what they
are doing.
Another participant stated that M4.0 is used to solve key business problems by bringing
products from idea to commercialization. She believes that by responding to trends and
market needs and customizing solutions for clients, they are achieving a competitive
advantage already. They create multi-year roadmaps to accelerate innovation and solve
problems continuously. They collect data and customer metrics to inform the road map.
So, they are essentially using the data to optimally serve customers and achieve a
competitive advantage.
How do you keep up? Another participant echoed the answer above—they listen to their customers and he is
almost constantly out in the field with customers, literally sometimes on roofs of
buildings. He never stops listening…the day he does, it will be over.
Another organization gets information in real time and uses this customer data on the
shop floor. They have customers on the floor providing feedback. The team also
engages with IT multiple times a day to leverage data. Teamwork helps them to keep
up.
Get your people to understand where you as an organization are going with M4.0, so
they too can talk about M4.0 with customers and colleagues. Educate them. The key is
to look at your operation and decide where the M4.0 baseline is. Where to inject it in
supply chain? Their first goal was to electronically monitor tooling. This saved them a
quarter of a million dollars over five years.
Manufacturing Leadership Council research indicates that technology is the “easier” part of M4.0. Survey respondents say it is relatively easier than the organizational and cultural aspects of embracing M4.0. Are the workforce issues easier or harder for your (SMB) company? HR decisions are tough. Personnel changes were necessary at my company. We had
issues with some staff -- including a star performer who was resistant to collaborating.
As we believe that collaboration is a cornerstone of M4.0, this was a problem. This
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person did eventually collaborate and help others and we moved forward, but it was
definitely challenging.
The people and cultural issues are not easier or harder in a small versus big company.
However, the ability to collaborate and change will impact the ability to succeed with the
rapid pace of change in manufacturing today.
What techniques did you use [improving processes and transitioning to M4.0]? There is definitely a communication dimension. Our journey began with watching machine productivity. This threatened some
employees but we explained to them that we were only trying to help and empower
them to be more productive.
One organization struggled with going paperless. Resistant employees were skeptical
until they heard from customers about how happy they were. This underscored the
value of positive feedback from the customer base and the importance of getting
ongoing feedback.
Provide basic examples of how M4.0 change and improvements can make the company
more successful and share these with your employees.
What about future requirements, such as understanding and defining new digital roles in your organizations going forward? SMBs will be competing for digital talent against larger companies and companies from other sectors. We need to market manufacturing as an exciting, growing industry! Make potential
employees understand that manufacturing is a high-technology place to be. Millennials
want meaningful roles in organizations, so create a purpose for them and cultivate a
culture of continuous learning to attract talent.
It’s true we have an aging workforce. We are looking for Millennials as they are tech
savvy. We need to give them responsibility. We gave a Millennial employee ownership
of a cross functional project – the boss works for the Millennial.
It’s also important to record the tribal knowledge every organization has. Get that data
into a system – make it part of cultural change.
Show the talent that at your company they can make an impact. Make clear they can
grow and engage.
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______________________________________________________________________
KEYNOTE The Future of Work in the Manufacturing 4.0 Era
PRESENTER
Caralynn Nowinski Collens, Chief Executive Officer, UI Labs
Member, Manufacturing Leadership Council
LinkedIn Profile
TIME
Wednesday, June 13, 2018 at 8:30am
______________________________________________________________________
SESSION ABSTRACT
As industry leaders, it is critical to understand the implications that manufacturing’s
digital transformation is having and will have on our existing and emerging workforce.
Participants discovered what skills and capabilities are needed to enhance productivity
across the manufacturing value chain.
KEY TAKE-AWAYS
Insights into the technical and soft skills necessary for digitalization in
manufacturing
Examples of emerging roles and corresponding use cases
Tools that your company can use now to prepare your workforce
INTRODUCTION
The conversation about a changing workforce isn’t new. The first and second industrial
revolutions changed the workforce too. Today we have the digital revolution and
automation. We talk a lot about technology, but the workforce is critical. People are the
most important thing.
OVERVIEW
The digital revolution is changing things faster than ever before. We are learning how to
use the tools of the future. And…if we are connecting everything, how do we secure it
all? Will there be people in our future factories and what will they be doing?
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Recently, the world chess champ was beat by IBM’s computer. The human was
disappointed, but realized there were options for computers and humans to work
together. Lesson: you need to be able to bridge the gap between humans and machines
and explore- cross functional and cross cultural learning.
KEY QUESTIONS
What will we do about all the coming changes in manufacturing?
Within the manufacturing process, where are the skills needed?
TAKE AWAY
There are many new digital products and processes: Digital management, cross-
capabilities, product life cycle in the digital thread, digital design, digital manufacturing,
digital products, and the digital enterprise
New futures, new roles:
Examples of new jobs - Chief Digital Officer, Digital Engineer, Model based
system engineer (MBSE), Predictive Supply Network Analytics Engineer
Examples of collaboration - Collaborative Robotics Specialist- how do you debug
these systems, how do you train people on these systems ex) AR/VR systems
specialist-
Example of new or transitioning role: Automating the creation of work instructions
for AR in manufacturing
We have 10 million manufacturing roles today, we need to make sure these roles
can be transitioned into the future
Most new roles do not need more than two years of training
o Example: Maintenance technician becoming a predictive maintenance
technician
Generation Z, going into college now:
65% of the jobs that they will take don’t exist today!
How to attract this new generation into M4.0?
Look for workers who are adaptable as there will be constantly changing
opportunities
Provide incentives to change and adapt, enroll in new programs
Executives say that only 14% of the workforce is adaptable
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KEY INSIGHTS
Understand the challenges and opportunities that M4.0 brings to the workforce
Realize what’s at stake - the future of your company, profit, jobs, wage growth
Even though we think of jobs as being taken away by digitalization, there are new
jobs coming and there is a skills gap for these jobs
o M4.0 will create 3.5 million new jobs and 45 billion dollars in new jobs
o New jobs created will be cross functional and require constant learning.
Therefore, the workforce demands will stress adaptability and encourage
learning
o Our workforce is retiring - how are we going to get their knowledge once they
are going
The gap between digital leaders and non-leaders is increasing…and digital
leaders are gaining more market share
Obviously, technical skills are essential. Robots will be used but somebody has
to program the robot
There will be a need for people with ‘soft skills.’ People who can cross
boundaries and understand the entire manufacturing life cycle
Think humans plus computers plus strong processes. This equals success in
Manufacturing 4.0
ACTION ITEM
Think about how to attract the millennial generation into these jobs
There is not much awareness of M4.0 in the public. Bridge the gap through
creating online classes and partnerships
Recruit people who are adaptable, as that is not a natural trait for most people
Encourage adaptability and learning through incentives or programs
Work in partnerships with universities or other resources
FINAL THOUGHT
In order to maximize the power of M4.0, it’s imperative that your company has a
workforce that understands this revolution and has the necessary skillset. What’s at
stake is the future of your company as well as profits.
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____________________________________________________________________
EXECUTIVE INSIGHTS New Insights into the Leader’s Role in Driving Safety Excellence
PRESENTER
David Crouch , Director of Research and Development, Caterpillar Solutions
LinkedIn Profile
Evan Sinar , Chief Scientist and Vice President, Center for Analytics and Behavioral
Research, DDI
LinkedIn Profile
TIME
Wednesday, June 13, 2018 at 9:00am
______________________________________________________________________
SESSION ABSTRACT
We’ve always known intuitively that leaders have an impact on employee performance,
but until recently we didn’t have a way to measure the critical few skills required for
effective safety leadership. Visibility to how individual leaders perform across four key
performance drivers can reveal specific opportunities to transform your culture. This
presentation provided a practical framework and research-based approach for
diagnosing and developing the leader capabilities that create safer workplaces.
KEY TAKE-AWAYS
An understanding of what is required from leadership to create a culture of
safety excellence
An explanation of the 4 critical leadership skills and the 14 elements within them
that build and sustain a culture of safety excellence
Learn how companies are utilizing safety leadership assessment data to
improve performance
OVERVIEW
David’s presentation examined the importance of a leader’s role in establishing the
overall safety environment at a company. He emphasized that leadership behavior is
massively impactful to the overall company culture. David believes, “As the leader goes,
so goes the team.” This should go without saying, but having this as an emphasis point
is not a given at all companies.
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TAKE AWAY
At Caterpillar, they did some analysis and learned that on a yearly basis 6% of their
workforce was getting injured on the job. That ended up costing them roughly ten
thousand dollars per injured person. That’s significant. This was brought to the attention
of the CEO in 2003 and ever since there’s been dramatic improvement. The safety
culture has been transformed and subsequently so has their bottom line.
But this seismic shift didn’t happen automatically. It took five years of research and
development. For Caterpillar to achieve Level 6 Safety culture, they had to begin by
examining how leaders behave on a daily basis. The company concluded that leaders
reacting, observing, believing, engaging, committing and then doing the safety leading
was a crucial trajectory.
Caterpillar arrived at Four Domains that leaders need to develop in order to foster
a safe work ecosystem:
Domain #1 - Drive accountability so that all workers know what is expected. This
required high quality training, appropriate feedback and the availability of the necessary
resources needed to work safely
Domain #2 - Centers on the concept of connectivity. If everyone understands safety is
integrated and information is shared, then an atmosphere of connectivity is established
Domain #3 - Built around the idea of demonstrating credible consciousness. Bottom
line, if the CEO is wearing a seatbelt, he makes sure that everyone else around him is
as well
Domain #4 - Is about building trust. This is simple; show care and concern for your
workers
ACTION ITEM
Leaders should make a point to be knowledgeable about the safety processes of
the team, including gathering all the necessary information to make smart
decisions
Armed with this, leaders are then able to effectively appraise risk as well as
internalize safety concepts and apply them personally
Accountability is a strong driver of a safer workplace
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It’s important to have defined safety expectations, to integrate all the safety
practices and finally, to share all the available information
BEST PRACTICE
Leadership has to have daily behaviors of safety to guide their team to a safety
culture
They need to display knowledge of what their employees are dealing with and
develop credibility and trust
Give clear, well-communicated safety instructions, and get the employee’s verbal
recognition of protocols
Work with consultants to drive team safety culture
TAKE-AWAY
CEOs or leaders who strive for a safe workplace will be rewarded with a more
robust bottom line
Money will be saved in dealing with workplace injuries and production will likely
go up
But, it’s crucial for leadership to practice what they preach and be knowledgeable
in all ways about the safety practices required of the team
FINAL THOUGHT
By fostering an atmosphere of rigorous workplace safety, companies can enhance their
bottom line while also creating a healthy relationship with their employees. Key to this is
having leaders who demonstrate real concern, are apprised of the safety standards, and
make information easily available to their staff.
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______________________________________________________________________
MANUFACTURING LEADERSHIP AWARDS SPOTLIGHT Selected Winners of the 2018 Manufacturing Leadership Awards
VARIOUS PRESENTERS
TIME
Wednesday, June 13, 2018 at 10:00am
______________________________________________________________________
SESSION ABSTRACT
Selected Winners of the 2018 Manufacturing Leadership Awards will give a short
synopsis of their winning projects: what was accomplished for their companies and
lessons learned.
Winner: Cisco Systems, Incorporated Category: Data and Analytics Leadership Project: Software Failure Analysis
Software issues are perceived as hardware defects in the field creating unnecessarily
RMAs and impacting customer’s satisfactions. Digital diagnostic signatures and RMA
rules as used to improve field awareness for the misperceived issues.
For open software bugs the journey was as follows… engage SW engineering – create
new defect, accelerate resolution for open defect, and perform test escape analysis.
Results:
1. A 40% reduction on software related RMAs
2. Warranty cost avoidance
3. Improvement in quality perception
TAKE AWAY
Hardware and software can’t be decoupled
Supply chain can provide a unique insight to software quality
New capabilities get enabled everyday as IT technology advances
If you are not feeling uncomfortable, you are not innovating
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Winner: LAI International Category: Enterprise Integration and Technology Leadership
Project: Factory of the Future
LAI has a nationwide footprint with four manufacturing facilities around the U.S. Their
company motto is “Accept No Defect, Make No Defect, and Pass-On No Defect.” LAI
needed a framework for their business as it applies to manufacturing 4.0. Many of their
production technology machine tools were of the legacy variety – always a problem for
integration and data extraction.
The question was: how to get old information to apply to business today? How to
connect all the technologies, and then what do we do with it? How does it translate into
an improvement? The goal was manufacturing and ubiquitous access. This required
integrating all information in order to come up with a commonality.
They worked on Data Integration Flow. This entailed getting information to the operator
of the machine. They leveraged a roadmap from Merck: Roadmap to Factory of the
Future (FOF) and M4.0.
Phase 1: Format and collect data. Focus on results Phase 2: Learning cycles. Adjust the company culture
M4.0 helped them deliver perfect parts at the right value
Winner: Lockheed Martin Corporation
Category: Smart Products and Services Leadership
Project: Fiber Optic Quality System
Most networks use fiber optics. This is a tremendous amount of data to contend with,
plus hundreds of thousands of cords.
Contaminants or defects can disturb data transmission. For example, airborne particles,
body oil, dust, scratches, chips. Maintenance of fiber optics requires inspection and
cleaning.
Challenges:
Detecting changes as small as 3 microns
The end phase of 5.8 to 50 microns
Pass or fail criteria
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Multiple connector interfaces
When cleaning, if you leave a defect, you will have loss of data. This required
new solutions from cleaning products. They collaborated to design and implement these
products.
Achievements
Reduced labor hours by 50%
In the past, labor would take 30 minutes or 4 hours for a full network
Now, down to 12 minutes
Reduced hardware rejections
Winner: Merck & Company, Incorporated
Category: Supply Chain Leadership
Project: Product/SKU Optimization
Merck’s award was for an SKU optimization project. At Merck, they don’t manage a
huge inventory of SKU’s. But it was the mix of the portfolio that was a challenge.
80% of revenue was coming from less than 2% of their SKU’s. Any SKU required
resources from manufacturing to packaging. They wanted to take better advantage of
their SKU’s:
Rationalization: get rid of what you don’t need
Harmonization: like for like products; reduce similar products
Governance: new approach
They approached the problem with an agile methodology that consisted of a
collaborative IT and business team executive approach. They had very quick results
with IT solutions that automated a consolidated view of data. But it would drift back.
To enable sustainment, they added accountability and visibility to the owner community.
They integrated business information and automated the workflow when decisions were
made, and enabled ongoing visibility in real time. The team had to continually adapt.
Results:
Saved $130 million, on a base investment of $3-4 million
Savings model in place to manage their SKU’s going forward
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Winner: Unity Scientific
Category: Engineering and Production Technology Leadership
Project: Reduced Complexity Assembly, Calibration, and Testing
Dr. Jerry Workman Jr. from Unity Scientific spoke and accepted this award that
pertained to food products chemical analyzation.
Product: SpectraStar. High Performance Low cost with DLP technology
Project goal: Make the highly complex easy. Necessity was the mother of invention.
They combined 3D printing and AI to make a machine.
Results:
Print on demand
Part count reduced by 50%
Inventory part reduced by 50%
o (Fasteners/pins/ in a classic Chassis) vs (3-D printed chassis)
Total assembly time reduced by 400%
TAKE-AWAY
Complex assemblies can be made easy
3D is the future of complex structures
Devices can be replicated perfectly
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______________________________________________________________________
CONCURRENT COLLABORATION ZONES - THINKTANKS Zone 1. Digital Twin Deployment – You Aren’t Alone
FACILITATOR
Fred Thomas, Director, Discrete Manufacturing Industries, Dassault Systèmes
Member, Manufacturing Leadership Council
MLC Profile
TIME
Wednesday, June 13, 2018 at 1:45pm
______________________________________________________________________
SESSION ABSTRACT
The Digital Twin concept of a virtual model that is the digital equivalent of a physical
product was first introduced 15 years ago by Dr. Michael Grieves in his work with
NASA. Over the intervening years, the concept has grown in its manufacturing impact
potential (and myth) as technology advancements have exploded. While there have
been some high-profile successes reported in industry media outlets, what is the reality
of Digital Twin deployments on the manufacturing floor? Is my organization the only one
that seems to be doing nothing on establishing a Digital Twin in manufacturing?
This interactive session identified the value of the Digital Twin as part of a successful
Manufacturing Operations Management strategy, examined the challenges associated
with successfully deploying a Digital Twin model across the manufacturing enterprise
and outlined a roadmap for starting a Digital Twin journey.
KEY TAKE-AWAYS
Key factors for establishing the value of the Digital Twin concept within my
enterprise manufacturing strategy
Examples of the underlying technologies that are important in creating a Digital
Twin-enabled environment
A framework for beginning the journey – what are the critical steps that are
needed now
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OVERVIEW
Moving forward, the concept of the Digital Twin and its usage in manufacturing is going
to be critical. The presenter referenced a book by Dr. Michael Grieves, Virtually Perfect,
which was described as “a deep discussion of not only Digital Twin but Digital Continuity
in the entire product lifecycle, emphasizing the importance of continuity from virtual to
physical space.”
What is Digital Twin?
“Virtual information constructs that fully describe a potential or actual physical
manufactured product from the micro-atomic level to the macro-geometric level.”
–Dr. Michael Grieves
Components of the Digital Twin:
Virtual model of real. Virtual representation of a physical object
When addressing the manufacturing of project:
o “It is cheaper to fail when you move bits around than atoms”
o The key is to be able to address the manufacturing of a product where it
costs the least, in the manipulation of that virtual model
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KEY INSIGHTS
By mirroring the digital model and the physical process on the shop floor, then updating
that model with the results of manufacturing, digital twin can radically transform the
business.
The Honda customer case story is an example of digital twin being an enabler of
business transformation and how they are handling the challenges in the automotive
industry: Honda Story for Manufacturing Simulation Expansion
Participant comment: “Digital twin is a visual representation, then sending telemetry
to make a product.” The clearest representation of digital twin is the “as built”
representation, but once they become cars with VIN numbers they become two different
models – different drivers, different maintenance, different tires etc. These products
become different once produced from the visual representation.
The simulation is the validation. Use your tools to simulate the process or process
execution. You can take the operational data from manufacturing and feed it back into
the virtual model and update it to the physical creation. With a digital twin product,
artificial intelligence provides a feedback loop to get you where you want to be. You are
introducing artificial intelligence into a feedback loop.
Why is Digital Twin of Value?
Digital Twin drives reduced costs. For example, additive manufacturing looks at the
weak points such as identifying areas/parts that can be corrected. There is a point of
diminishing value and digital twin will be there to self-correct the process.
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Where do we see the value? Essentially, in being able to shorten the time to bring new
products into production. Speed, agility, lowers the cost. Validating in a virtual space is
less expensive than working with physical prototypes.
There will never be a fixed point when you are done. This is a journey that never ends
Due to technologies always advancing, it is ever evolving. This is not about technology
it’s about your business.
Doing nothing puts you at risk in the long term. Digital Twin is an enabler from a
strategic planning perspective and a policy deployment perspective. In our competitive
world, we need to bring products to market faster, this is critical to success.
IMPLEMENTATION GUIDELINES
How Do I Get Started?
Avoid the “shiny ball approach.” A strategy is needed, start with a business assessment
first. It is not recommended to do all the assets, but to identify the key parts that need to
be monitored and create the digital twin for them.
A recurring theme of connectivity and continuity is required in your environment. There
are ways to look at legacy equipment if you have a digital strategy, you can do this if
you go back to basics. The same discipline can be applied to products, to systems and
to processes. You need a realistic assessment and benchmark.
Talent is also a part of the equation. The next generation of manufacturing personnel
is already familiar with configuring avatars and high end gaming capabilities. There is
an expectation there. There will be lessons on concept configurability so that the
environment can be visualized, played with, configured, and experience failures.
Many companies have additive manufacturing initiatives, to look beyond just one piece.
In one organization, additive is being used in rebuilding and where a rebuilt part is being
put back on the road for another several hundred thousand miles.
FINAL THOUGHT
Digital Continuity is no longer an academic exercise, companies need to embrace the
technology and determine their strategy for their business to optimize operations and be
cost effective. Digital Twin is an enabler. It is a journey and with evolving technology, it
will never end. This is about business, not technology. Better to be business driven
than technology driven.
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______________________________________________________________________
CONCURRENT COLLABORATION ZONES - THINKTANKS Zone 2. Edge Computing in Manufacturing 4.0
FACILITATOR
Hugh Arif, Director, Industry Solutions, Manufacturing Practice AT&T
LinkedIn Profile
TIME
Wednesday, June 13, 2018 at 1:45pm
______________________________________________________________________
SESSION ABSTRACT
Manufacturers can create 2 times as much data as other industries. As companies enter
the dawn of the age of Manufacturing 4.0, the proliferation of connected devices can
add complexity to protected, digital transformation strategies. This Think Tank session
discussed edge computing in the manufacturing environment and explored the
technology implications of virtualization and the cloud, the Internet of Things, and multi-
network communications.
OVERVIEW
Cloud Computing has been around for a while, but now AT&T and other organizations
are focusing on edge computing. Edge computing devices are becoming more powerful
so it requires bringing more storage to where users are versus it all being transmitted
into the cloud.
Let’s answer the question… what is edge computing? Essentially, we are now pushing
the frontier of data applications away from the cloud and bringing it to the ‘edge,’ near
the place the computing is actually happening. In other words, the computing
infrastructure lives close to the source of data. It brings the data closer to the
manufacturer.
Why should you be interested in edge computing? Well, now manufacturers are
collecting massive amounts of data and indexing all of it. There’s too much to push out
to the cloud. Consequently, there has to be some kind of filter so, essentially, we’re
trying to reduce data.
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TAKE-AWAYS
AT&T has established a new manufacturing practice and is looking to extend
relevance to their services and products
Demand Driven Manufacturing is driven by EDGE computing. Bringing the Data
closer to where the users are is the new practice versus storing data within the
cloud only
Domain 2.0 is the shift from hardware to software. A good example is loading
applications OTA to your iPhone and then deleting as needed using iTunes
SDN / NFVs are being replicated in the cloud verses being executed in a router
or switch
Moore’s law is the theoretical law behind the shift from hardware based
computing to virtual computing
KEY QUESTIONS
Why EDGE? Questions and comments from the audience:
When collecting massive amounts of data for learning - how can we filter the data
and prioritize?
Sensors and data, how do they interact? Where is the convergence happening in
the network?
Is there a demand to move data lakes to the EDGE?
SaaS is starting to take hold in manufacturing and is it fully functional
There are clearly learning gaps in managing EDGE devices. Tapping into remote
mentoring solutions helps educate junior techs on managing legacy PLC
applications
o Use Case - Corning Glass using EDGE cloud for supplier access
IMPLEMENTATION GUIDELINES
Ask: Do all devices really need to touch the Internet?
If EDGE is the inroad to additional services, than security is paramount
M4.0 prototyping is huge – crawl before you run and fail fast practices are
prevalent
Site typing practices are happening in order to determine the correct connectivity
Data traffic priority is a huge concern and should be a component of site typing
The repurposing of hardware people into software-defined networking (SDN)
people is happening
Additional training services are needed to transform the workforce to support
SDN
o Some companies are using local schools curriculum to target recruiting efforts
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FINAL THOUGHT
The pervasive thought with edge computing is how to maintain security when you’re not
relying on the cloud but instead keeping the data out there ‘on the edge’, near to the
manufacturer. There’s also the notion of software handling data versus hardware
handling it. What does this all mean for the future?
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_____________________________________________________________________
CONCURRENT COLLABORATION ZONES - THINKTANKS Zone 3. A Renaissance in Product Design and Manufacturing: The New Role of Generative Design
FACILITATOR
Mark Davis, Head of Design Research, Autodesk Incorporated
LinkedIn Profile
TIME
Wednesday, June 13, 2018 at 1:45pm
______________________________________________________________________
SESSION ABSTRACT
For decades, the process of product development has been painfully repetitive and
rigid. Designers and engineers would take the customers’ requirements, create a few
design concepts, experiment with possible forms and materials, test designs virtually
and physically to determine how they held up in various conditions, and iterate until they
ran out of time or money. That’s all about to change. In this interactive discussion, new
technologies were presented and shifts in mindset were examined. New processes that
will be required for companies to take advantage of generative design were discussed
and participants learned why now is the time for those in manufacturing to begin laying
the groundwork for this future of intelligent design automation
KEY TAKE-AWAYS
Discover how generative design will disrupt traditional design methods
Learn how professionals in industries such as automotive and aerospace are
already using generative design tools to compete more effectively
An understanding of the progress and rate of change with generative design for
manufacturing
OVERVIEW
Generative design is an iterative design process that includes a program that will
generate a certain number of outputs that meet certain parameters and a designer that
will fine tune it by changing values and variables. This can be done on a machine like
a digital computer, or it can be conducted by a human with pen and paper.
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TAKE AWAY
Generative design is becoming more important, largely due to new programming
environments
Only a few of the participants had heard about generative design
Goals = Feasibility versus Technology versus Viability versus Desirability
Artificial Intelligence is at an inflection point for design and manufacturing
KEY QUESTIONS
1. What is the process and rate of change in AI for design and manufacturing?
2. How will Generative Design disrupt traditional methods?
3. How might we leverage this change to compete?
KEY INSIGHTS
Invest in the problem definition
Problem definition gets richer over time
Generative design is not topology optimization
Generative design is a feature of design and not a product
BEST PRACTICE
1. Define
2. Generate
3. Explore
4. Make
ACTION ITEM
Where to start
1. Change in mindset
a. Retrain toward problem definition
2. Start with a small team
a. Focus on collaboration between disciplines
i. Conceptual designer gets clues on cost at the conceptual design
phase
ii. MFG engineer can see backup streams from the conceptual design
phase
3. Explore manufacturability of different solutions early
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FINAL THOUGHT
Problem definition is important from the design point-of-view. The convergence of
design and manufacturing is when the computer ‘gives’ you the solution with creative
artificial intelligence giving you a competitive advantage. Human + machine = better
then human alone.
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____________________________________________________________________
CONCURRENT COLLABORATION ZONES – THINKTANKS Zone 4. Optimizing Assets through Predictive Maintenance
FACILITATOR
Lubor Ptacek, Vice President, Product Marketing, ServiceMax
LinkedIn Profile
TIME
Wednesday, June 13, 2018 at 1:45pm
______________________________________________________________________
SESSION ABSTRACT
Predictive analytics and service delivery can help manufacturers increase equipment
uptime and ultimately increase customer satisfaction. Analyzing sensor data to predict
when maintenance is required enables service organizations to transition from reactive
to proactive service. The data gathered during the service delivery can be used to
further optimize the asset data model, leading to more reliable equipment and ultimately
to happier customers. In this interactive session, Lubor presented ideas, experiences,
and challenges and let participants in a discussion about where they were on their path
of digitization through predictive maintenance and how to get to the next level.
KEY TAKE-AWAYS
Insights about the key strategies for transitioning from reactive service to
predictive maintenance
Examples of the challenges in leveraging IoT to deliver predictive maintenance
Best practices for dealing with the data ownership issues in the IoT world
OVERVIEW
Reactive service/break fix is not a good situation and something we need to avoid at all
costs. The customer experience and primary customer mission suffers. Satisfaction,
money and sometimes people’s lives are on the line in this situation. Ultimately
everyone wants and needs a more proactive approach. You need to do it in a proactive
way (service).
The question becomes: How do we get from reactive service to proactive service?
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Reactive Service
Break -- fix
Dissatisfaction
Money spent
Want to avoid
Proactive Service
Do it at a time / way that is convenient
Proactive service/maintenance:
o Preventive (planned)
o Condition based
o Predictive
Where to start?
1. Identify key problems in your line- lost function/lost time
2. Find key parameters
3. Analyze those problems
4. Predict the how’s
Failure frequency and cost
Identify a cost level which will impact operations
Graph of cost on x axis, frequency on y axis
Manufacturing, field services
Things you don’t know, or ‘invisibles’
Bad/broken/bankrupt
Need correct details
Example: Data collected from a wind turbine is wrong if it’s not noted that ice is
on it
In order for all of this to happen, the Internet of Things must be utilized.
There are thousands of sensors in every piece of equipment- we need a way to
send this info /get data from it
o What do we do with this data? This is where analytics come in, and these
analytics are a necessity
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TAKE-AWAY
In terms of analytics:
Do you want to monitor everything?
How do you identify the most critical thing to do? What method do you use
today?
How to prioritize?
Customers are overwhelmed in the beginning because they have so many items
You do things in parallel
Focus on the high value equipment
Many participants at the session suggested they prioritize their top three issues, but
what about issues you are not aware of?
How do you know your asset is working in the way you want it to be?
You need to be able to optimize:
o The quality of the parts
o The output a part is producing
o Uptime
You must create your own assessment chart on how good your assets/production line
is. From there, you can decide next steps to take.
KEY INSIGHTS
It’s easy to get overwhelmed with the quantity of alerts from IoT…not all of them
are important
Need data analytics to filter the data
IMPLEMENTATION GUIDELINES
Prioritize your problems
Focus on the high-value items
Identify your position on a failure frequency and cost chart
FINAL THOUGHT
Predictive maintenance – the machine will tell you when it needs to be fixed
Predictive model – optimizing the service
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_____________________________________________________________________
CONCURRENT COLLABORATION ZONES – THINKTANKS Zone 5. Will Blockchain Transform Your Supply Network?
FACILITATOR
Irene Petrick, Director of Business Strategy, Intel Corporation
LinkedIn Profile
TIME
Wednesday, June 13, 2018 at 1:45pm
______________________________________________________________________
SESSION ABSTRACT
We tend to think of supply chains as linear and unidirectional. It could take weeks to
trace a product back to its origin, if possible at all. Today, with the introduction of
distributed ledger technology—blockchain— industry can realize the benefits of near-
instant proof of origin, tracking and tracing, order status, and quality assurance. The last
18 months have been pivotal in supply chain management as industry experiments with
the benefits of blockchain in creating irreversible, distributed records. This session
explained blockchain and focused on new applications for managing dynamic, non-
linear supply chains.
KEY TAKE-AWAYS
An understanding of how blockchains help ensure status of goods in transit and
will ultimately be relied upon to certify quality
Insight on unique data and contract privacy requirements for enterprises
Best practices for identifying the attributes of your supply network that could be
supported by blockchain solutions
OVERVIEW
Any blockchain network is simply a community that makes transactions transparent to
all members of that community, and is governed by all. Every participant has an
updated and identical copy of every transaction that was ever recorded to the ledger,
making it virtually impossible for a single participant to alter data behind the scenes, and
eliminating any single point of failure in the network.
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At its essence, blockchain offers tamper proof asset tracking and logistics among
multiple mutually distrusting participants. This will undoubtedly contribute to dynamic
supply chains, new exchanges, reduction of reconciliation time and expenses, and
potentially new revenue streams.
Because the technology and the ecosystem are in development—particularly beyond
cryptocurrency into the supply chain space – it is critical to pay attention to your own
requirements, partners, and context, and ensure the solution that you select for a pilot
or proof of concept (POC) can improve supply chain transparency and will result in a
positive ROI.
KEY QUESTIONS
How mature is blockchain beyond cryptocurrency?
What kinds of use cases are common?
What do we need to watch out for as we embark on POCs?
TAKE-AWAY
Blockchain, though not a new technology, is relatively new in supply chain
applications, and the ROI has yet to be clearly established
The most common use cases are around provenance, traceability, and the
emerging quality assurance and compliance
It is anticipated that blockchain will help save cost when it comes to disputes and
reconciliations among supply chain partners
New revenue streams could come from increased visibility throughout the supply
chain and quality assurance guarantees; however these may initially be limited to
high value assets or IP
POC’s should be carefully planned to consider: scale deployment costs, data
stewardship, data assurance, IP ownership, and permissioned/enterprise
networks
KEY INSIGHTS
Blockchains hold tremendous potential, but are still nascent in supply chain
applications. We should not consider them a panacea, but rather as a tool that enables
the formation of communities that can exchange information and coordinate action—
and track all of that data in a tamper-proof record—enabling mutually distrusting parties
to interact without an intermediary.
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It is our job now to determine whether converting portions or entireties of our supply
chains to run on blockchain will result in sufficient cost savings or incremental revenue
generation to warrant their deployment.
SOME USE CASES SHARED BY PARTICIPANTS
Provenance, QA, Process Improvement: Tracing product or component origin,
including which process or inputs affect my product, e.g. foods the cow eats
affect the consistency of the cheese—tracking down to cow and farm level—so
they can optimize product mix. Still exploring value add versus cost to implement
Accountability and Traceability: Track something like temperature in the food
chain from farm/factory, to 3PL, to shop, to table. If degradation can occur, I can
more quickly resolve liability or billing disputes
Minimize Billing Disputes and Time to Reconciliation: Track freight as parts
move sub tier to sub tier throughout supply chains. 1) Ensure we only pay for our
own freight. 2) track parts we sell to customers that get refurbished so we
optimize re-use without over-use
Country Regulation Compliance: Mandatory certifications that blockchain can
prove your product is in compliance with country regulations as you import.
Forecasting based on End Customer Demand/Use: Data coming back would
add value to the initial manufacturer
IMPLEMENTATION GUIDELINES
Who owns the Blockchain? Everyone who uses it. We’re used to supply chains
where someone is in charge. Who owns the data? Sensor maker? SI who installs
sensor? Company on whose equipment the sensor is installed? End consumer?
You need to determine what data matters and who’s supplying it
Who owns the IP? If we can’t solve this problem we’ll see lagging adoption
Blockchain Generally Presupposes Connectivity to Update the Chain. How do I
Transmit Data from a Remote Location? You have to think about communication
channels you’ll use, what bandwidth is available to get data uploaded
Where are my points of failure? This is where you should put your effort in the
POC to determine whether the investment in blockchain is worth it
How can I qualify high value parts? Jet components, and 3D printer outputted
parts will require functional parts and a pedigree associated with that since they
are low volume parts, generally with expensive materials, where we don’t want to
do destructive testing
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FINAL THOUGHT
Blockchain is still early in supply chain applications. Likely tracking and tracing within
agriculture will be the tipping point beyond cryptocurrency. We’re not expecting prices to
rise because we expect blockchain will help reduce disputes and speed up
reconciliation.
Now is the time to set up POCs and understand whether the reduction in dispute and
reconciliation costs outweighs the transition to a new process methodology, or if you
can in fact generate new revenue models or entire paradigm shifts in how you deliver
value to customers.
Keep in mind:
Privacy: How will you protect IP, identity, during and after an engagement?
Scalability: Do you have a path to deployment once the POC is complete that
can take advantage of existing compute resources that are easy to scale up?
ROI: Focus on the hardest parts first, to determine whether there is incremental
value. Are you saving cost or considering new revenue streams or business
models?
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_____________________________________________________________________
EXECUTIVE INSIGHTS Blueprint for Disrupting Your Culture and Turning Employees into Innovators
FACILITATOR
Alex Goryachev, Senior Director, Corporate Strategy and Innovation Group,
Cisco Systems
LinkedIn Profile
TIME
Wednesday, June 13, 2018 at 3:10pm
______________________________________________________________________
SESSION ABSTRACT
To keep pace with rapid changes in today’s digital age, every company must reinvent
itself, disrupt its entire workforce and transform into a companywide culture of
innovation. Innovation can come from anyone anywhere, and the most brilliant game-
changers often bubble up from diverse employees with passionate ideas. Participants
learned how to ignite a grassroots movement across all functions in organizations of
any size or type to enable employees to think and act like entrepreneurs in a startup.
KEY TAKE-AWAYS
Proven success factors to jumpstart an innovation revolution that drives an
entrepreneurial mindset companywide
Award-winning, best practices that engage and inspire all employees to tap into
their purposes, and bring winning ideas to life like collaborative entrepreneurs in
a startup
Barriers to success, metrics, and lessons learned to sustain continuously
improving innovation programs
INTRODUCTION
Prior to Cisco, Alex Goryachev worked at IBM, Pfizer, and Napster. Alex spoke about
the business case for innovation, how Cisco innovates, and how to help employees
connect with their passion and drive innovation.
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OVERVIEW
Today, if you don’t operate under the principle of ‘disrupt or be disrupted’ you are most
likely setting your company up to fail. Forty percent of today’s Fortune 500 companies
won’t exist in 10 or 20 years. Recent examples of once prospering but now defunct
companies include Blockbuster, Circuit City, Lehman Brothers, Bear Stearns, and
Kodak. All are no longer here. How did this happen? Big companies get comfortable
because they are ‘old and wise,’ but develop tunnel vision.
Remember when there were taxis everywhere. And we couldn’t envision a world without
them? Then Uber and Lyft came along and now they are practically gone. Now it’s an
oddity to see one around town. The same principal applies to the phone, television and
media. Now there’s Hulu, Nextflix, Skype, Facebook, Whatsapp. Retail stores have
largely gone the way of Amazon. You have to ask, “Who’s going to own our space in
the business tomorrow?”
…Disruption wins.
ACTION ITEM
Think about how all these factors feed into each other:
Market disruptors
Hyper connectivity
Speed of innovation
The lower cost of innovation
Access to funding
TAKE AWAY
Cisco innovates using a 5 Pillar Approach:
1. Build
2. Buy
3. Partner
4. Invest
5. Co-develop
A key component of this 5 Pillar Approach is developing talent, which is vital. Also
crucial is figuring out how to leverage the ideas of CEO’s from companies acquired. It is
about getting employees involved, which means co-developing. Cisco does this by
providing access to tools at Cisco Innovation centers and/or encouraging employees to
partner with universities.
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It’s important for companies to think like start-ups but scale like enterprises. At Cisco,
the goal is to empower all employees to innovate. This mandate is supported by human
resources as well as corporate strategy. The philosophy is, let’s get everybody at the
company to share ideas. When this happens, it stimulates a network of people who are
passionate about something.
Cisco uses a Rapid Innovation Process:
Meet online
Employees call each other and talk about priorities
Ask for employee ideas
A 200 person team and 30 ideas move forward
If you are a part of those 30 ideas, you can see any executive at the company
Then they validate ideas with customers
Other Cisco take-aways:
They acquire a few companies every quarter
They partner with universities and start-ups
They invest in companies and accelerators
They develop innovation centers
They drive revenue through non-traditional means
They give structure and guidance to employees to innovate
They utilize practical trading - pair trades with customers on real problems
They foster non-traditional member relationships
KEY INSIGHTS
Drive innovation
Innovation is survival…constant changes can be the norm
Ask everyone to play a role: founders, ‘angels’
IMPLEMENTATION GUIDELINES
Create:
Innovation Programs
Mentoring Programs
Rewards
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FINAL THOUGHT
The reality is you can’t mandate innovation, but you can create an environment where
employees can feel passionate about something. At Cisco, the trick to fostering an
inclusive, creative atmosphere is to provide everybody with a role, a stake. At Cisco,
you are a teacher or a mentor or a creative, designer…. This produces a culture where
innovation is on everybody’s mind and everyone is invested and engaged.
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____________________________________________________________________
BOARD OF GOVERNORS PANEL DISCUSSION Factories of the Future
MODERATOR
Paul Tate, Co-Founding Executive Editor and Research Director
Manufacturing Leadership Council
LinkedIn Profile
PANELISTS
Dr. Dean Bartles, Director, John Olson Advanced Manufacturing Center, University of
New Hampshire
Member, Manufacturing Leadership Council Board of Governors
LinkedIn Profile
Dr. Jay Lee, Professor of Advanced Manufacturing, Ohio Eminent Scholar, and L.W.
Scott Alter Chair Professor, University of Cincinnati
Member, Manufacturing Leadership Council Board of Governors
LinkedIn Profile
Dr. Jim Davis, Information Technology and Chief Academic Technology Officer, UCLA
CIO Advisor/Governance Board, Clean Energy Smart Manufacturing Innovation Institute
LinkedIn Profile
Dr. Detlef Zuehlke, Chairman, SmartFactoryKL Technology Initiative and Scientific
Director, Innovative Factory Systems German Research Center, Artificial Intelligence
(DFKI)
Member, Manufacturing Leadership Council Board of Governors
LinkedIn Profile
Dr. Larry Lapide, Research Affiliate, MIT Center for Transportation and Logistics
Member, Manufacturing Leadership Council Board of Governors
LinkedIn Profile
TIME
Wednesday, June 13, 2018 at 3:40pm
______________________________________________________________________
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SESSION ABSTRACT
How will Factories of the Future be organized and managed in the Manufacturing 4.0
era? What are the implications for the way data will be used, production networks
operated, new business models created, and manufacturing enterprises structured over
the next decade? An expert panel of leading Manufacturing Leadership Board members
shared their insights and predictions on the ways that increasingly digitally automated
factories and data-driven manufacturing enterprises will be transformed over the next 10
years.
KEY TAKE-AWAYS
Expert insights into the new data-rich production models that will drive the
Factories of the Future
Examples of the key Manufacturing 4.0 technologies that promise to have the
most transformational impact on both plant floors and supply networks
An understanding of enterprise-wide implications for manufacturing industry
leadership, structures, and cultures
Moderator: How does the future of the factory look? What is likely to impact the future factory? In the past, whenever there was potential for conflict, a customer would call and ask, “If
we needed production ramped up, what would happen?” Then we’d call the suppliers
and then they’d call their supplier… Imagine the manual chaos of this…What if we could
do all this in real time? We’d know who could ramp up fast within minutes. That’s my
vision for the future of manufacturing. Total transparency in real time; how fast and who
can accommodate. Manufacturing 4.0 should let us all have that capability, now only a
few companies can do this.
We occasionally have something called drift. Wouldn’t it be great if the next machine
new about the drift and could compensate! That kind of capability is what I envision for
the future.
Let’s look at any point -- next year, five years, ten years out?
We came up with a roadmap for this… A key barrier is the increasing complexity of
having to interconnect more and more systems together. Get data in the right format to
the right people across the enterprise. We need to get out of so much effort with
stitching data together and into a mode of innovation with data. We also need workforce
skills to work with all the data.
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In the future, there will be no distinction between IT and OT. As per the business
practice side of things, they’ll learn how to work together so there’s a win-win. They are
not usually aligned that way now. We hope to re-use data sets and information systems.
The bottom line is a data driven environment for manufacturing.
What about the Factory of the Future, in supply chain economics? I am not a manufacturing expert but I am a supply chain expert. Unfortunately, we still
have the Henry Ford mentality today: Build a big plant and serve the world until you
build another big plant. This is great for western civilization, but not for the developing
world. It’s not sustainable. Bottom line, we’ll run out of resources.
U.S. citizens use five times more resources than the rest of world. One solution is small
plants and production in the future. The earth can’t support the population boom,
especially the way the U.S. consumes resources. The aging of the world shows that
developing countries are getting older, and undeveloped ones are getting younger.
Undeveloped countries have the labor we need. We have to build it where they are, and
they have to be small plants. We need a network of manufacturing plants that’s close to
consumption.
What about the Factory of the Future, in data analytics? My vision is to move from experienced-based to evidence-based management. To shift
focus from the visible to the invisible issues. To move from a traditional practice-
oriented, lean manufacturing approach (with problems, end-goal) to a worry–free
(avoidance) approach. The machine tells me how it is behaving. In the future, we need
to become more predictive and resilient.
This has become a transformational trend on a global basis- what is your view? Have a vision -- identify levels, build technologies -- make use of these technologies.
Manufacturing 4.0 is just part of the transformation of our lives. Data is fueling
everything. We must take care of data and learn how to handle it.
We’ve been talking about transformation. What is the payoff for companies?
Data.
Cost, productivity, efficiency. Moving from problem solving to problem avoidance.
Eventually we’ll be talking about a software platform. Stop managing problems, create
value now because of the data we have.
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We have information in milliseconds, but need to compete with companies wherever
they are in the world. Enable companies to play the right role on global stage.
Manufacturing 4.0 is the enabling vision we need. But, at the end of the day, earn
money and avoid somebody disrupting your business.
There’s a digital representation that takes place. We now have supply networks that
never touch the manufacturing products.
The payoff, the overall productivity will increase – that’s the payoff. Sensors to monitor
manufacturing = data to improve performance and improve productivity. You want to
stay in business; otherwise the customer will go somewhere else. So productivity is the
ultimate payoff.
Find the weakness of operation in terms of where you want to go. Then prioritize to fix
that weakness.
3D printing is its own supply chain and the future.
Make data a key asset. Think about good data and small data. Think about small data
growing into big data. Think of data as key asset.
What’s better about the products you are producing and the cost? Normally, we are looking at the bottom line level. Manage these issues - value creation
- don’t just manage problems - find value in why your issues are happening.
So, how do you measure that? Inward: savings. Outward: sell machines that give more value.
We’ve all got to make money out of this… New business models? We are competing in worldwide markets. Digitalization means immediate information
that people can compare. This new situation is the need. If you don’t do it, you’ll lose
business. Keep up and be prepared for the new world.
How to distribute? Look to Amazon, for example, the virtual retailer. Physical flow is getting disconnected
from the virtual world, because virtual suppliers, manufacturers, distributors, and
retailers are major players in the new supply chain.
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Business case to do that? There’s nothing you can do to plan for that. But scenario planning… technology should
be an enabler. What capabilities do I need and will M.4.0 enable that to happen?
If you were going to pass on advice to the audience about getting started, what would you recommend? Start with the low hanging fruit - network, information, Manufacturing Leadership
Summit, think long-term about your vision; not just first stages.
Find your current weakness; goal is to be worry free, prioritize first.
3D printing is the Holy Grail because we need a distributed global manufacturing model
with lots of small plants close to points of consumption.
This event is unique… 95% have NOT heard of M4.0 … where to start? Just start. Pick
a good problem and start using data and treating it as a key asset. And think about
small data growing into big data not starting with big data. Think about good data.
Experience what it’s like to work with data.
I hear from SMB’s about data being unaffordable. Hang in there. Open source data is in
the future.
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ABOUT THE MANUFACTURING LEADERSHIP COUNCIL
The Manufacturing Leadership Council, part of Frost & Sullivan, offers an integrated
portfolio of leadership networking, information and professional development products,
programs, and services for industrial executives worldwide. Our mission is to help
senior executives define and shape a better future for themselves, their organizations
and the industry at large. MLC’s portfolio consists of the Manufacturing Leadership
Council, an invitation-only executive organization; the annual Manufacturing Leadership
Summit; the Manufacturing Leadership Awards program; and the Manufacturing
Leadership Journal. For more information, visit us at www.gilcommunity.com/about-us
ABOUT FROST & SULLIVAN
Frost & Sullivan, the Growth Partnership Company, enables clients to accelerate growth
and achieve best-in-class positions in growth, innovation and leadership. The
company’s Growth Partnership Service provides the CEO and the CEO’s Growth Team
with disciplined research and best-practice models to drive the generation, evaluation,
and implementation of powerful growth strategies. Frost & Sullivan leverages over 50
years of experience in partnering with Global 1000 companies, emerging businesses
and the investment community from more than 40 offices on six continents. To join our
Growth Partnership, please visit www.frost.com.
DISCLAIMER
These Chronicles discuss key insights and take-aways from the 14th Annual
Manufacturing Leadership Summit: Accelerating the Transformation to Manufacturing
4.0, held June 11 - 13, 2018, Hyatt Regency Huntington Beach Resort and Spa,
Huntington Beach, CA. Frost & Sullivan makes every effort to ensure the quality of
individual session Chronicles; however, the summaries presented in the articles are the
expert opinion of the writers, and inclusion/exclusion of specific material is at the
discretion of each speaker. For more details, visit www.frost.com/ml. Frost & Sullivan is
not responsible for the loss of original context or the accuracy of the information
presented by the participating companies.
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