Digital Manufacturing and Design Innovation Institute
William P. [email protected]
"I’m here to announce that we’re building Iron Man…
Not really. Maybe. It’s classified."
—President Obama
$320 MILLION$70 million cooperative agreement with the U.S. DOD and matching $250 million from industry, academia, government and community partners.
6 OF THE TOP 20 Engineering schools in the country, with more than 12% of all engineering & computer science students graduating annually in the U.S.
220,000Partners, and more, ready to connect with the more than 185 small and medium sized businesses that have joined already.
MORE THAN 315 Local, regional, and national organizations, community colleges, and MEP networks have committed their support.
The Partnership
500+ CompaniesCommitting to participate.
HISTORICAL MANUFACTURING
• Linear process through design, make, and deliver• Commoditization of labor
TODAY’S MANUFACTURING
• Materials: Rising costs and supply constraints
• Production Overcapacity: reduced profitability
• Labor: Increasing costs globally, skills gap
• Outsourcing: separation of designers and makers has slowed innovation
• Barriers for Sharing Data and Information: technology, skills, incentives, security, trust, IP, standards
FUTURE MANUFACTURING
• Digital link between design and fabrication
• Connected machines, factories, and supply chains
• Transparency into supplier factories
• Data aggregation, analysis, and action across the product lifecycle
• Leverage the power of data analytics and networks to do more with existing resources
Manufacturing already generates more data than any other sector
Insurance
Education
Retail
Communications and Media
Banking
GovernmentManufacturing
Healthcare
Securities and Investment Services
Professional Services
Transportation
Resource Industries
Utilities
Wholesale
Construction
Consumer and Recreational Services
87116
166207245256273276
375336
397424
776773
9111,812
Annual new data stored by sector, 2010
1 Discrete manufacturing constitutes 1072 petabytes; Process manufacturing 740 petabytes
SOURCE: IDC; McKinsey Global Institute analysis
Petabytes
WHAT IS DIGITAL MANUFACTURING?
11001011
PRODUCT LIFECYCLE
11010010010001111011010101111011111011010110110100001010010010001111011111010101111011111010111110
1111
FABRICATE
FABRICATE
0101010011010101011011010101001001001010010010001111010101011110111110101111101111101011111011011010101010100000110101010110110101010010100100101111010100100011110101011110111110101111101111101011111011
111010001001010101111010101001001000111101101000100100011010101011011010101000101010110110101101001111011111010111110111110101111101111101011111011101111011010011110111011010101010110010110100100011010101011011010101001001000111101010010100100100011110101111111101111101011111011111010111110111110101111101111
101011111
ASSEMBLE
AFTER-SALES
SERVICEQUALIFY
SELL &DELIVER
END OF LIFE
REUSERECYCLE
FABRICATE
DESIGN
FABRICATE
DATA ACROSS THE PRODUCT LIFECYCLE
DATA
INFORMATION
DECISIONS
VALUE
Utilization of high performance computing to model materials, products and processes to enable “design with manufacturing in mind”.
INTELLIGENT MACHINING (IM)
ADVANCED ANALYSIS (AA)
Integration of smart sensors and controls to enable equipment to automatically sense and understand current production environment in order to conduct “self-aware manufacturing”.
ADVANCED MANUFACTURING ENTERPRISE (AME)
Information systems integration throughout the product lifecycle.
Digital links between design and fabrication.
Smart factory and supply chain management.
THREE FOCUS AREAS
OPEN SOURCE PLATFORM
An open source software platform that enables data aggregation, analysis, and action.
DIGITALCOMMONS Meet industry and national
needs for security, trust, and IP protection within the manufacturing environment.
CYBERPHYSICAL
CYBER PHYSICAL SECURITY
DMDII Technology Thrust Areas
DMDII Guiding principles
A
B
C
E
D
F
Start with the business need: Entire strategy is focused on how the application of advanced manufacturing technologies can solve specific business problems (i.e., “market pull” versus “technology-push”)
Build and cultivate a diverse, distinctive, industry-led team: Assembled collaborative & committed team of advanced manufacturing firms across sectors, large & small, public-private. Flexible models to allow everyone to participate.
Co-create the value proposition & strategy: Enlist the industry partners to define the strategy, operating model, project approach to build buy-in along the way
Build an aligned industry roadmap: identifying a common set of problems across partnership, and aligning on an industry technology and project roadmap
Bias to action… and creating demand: place a premium on speed and efficiency in launch and operation, getting to tangible impact soon through demonstration projects, which show what is possible and create demand for broader adoption
Self-sufficiency through impact: doing the above will yield a high-value institute, that will create value – not just from membership fees, but from value it creates
Despite the recognition of importance for digital design and manufacturing, most organizations feel they lack the necessary capabilities
14%
81%
Organizations with "high" digital capability today
Participantsindicating digital ops is a critical driver of future competitiveness
We surveyed decision-makers on where value will come from and their current level of maturity
▪ The survey leverages a detailed library of ~100 potential drivers of value along the value chain… as well as prompting for additional levers
New business creation
Product develop-ment
Sourcing Production Supply chain Service End-of-life/
disposal
ExampleDrivers
▪ Tracking and vis-ualization for the "reverse logistics“ supply chain for part disposal
▪ Predictive analytics for field main-tenance
▪ Real time product use/tracking in the field
▪ Real-time data collection/ analysis & operator feedback
▪ Advanced quality con-trol/analysis for process optimization
▪ Supplier identifica-tion & selection
▪ Cost trans-parency
▪ Contract compliance
▪ Collabora-tive innova-tion, i.e., crowd-sourcing
▪ Advanced modeling and simula-tion tools
▪ “Smart” products that send/ receive data during use
▪ New service business to leverage data
▪ Joint plann-ing and forecasting
▪ Inventory & working capital optimization
▪ Customer demand-sensing
For each step of the value chain (with particular depth in manufacturing production), the tool identifies a. The most important areas of opportunity in your organization b. Current organizational maturityc. Current improvement projects underway
Quality
Cyber security@
Marketplaces and web-platforms
New business creation
Sourcing Capital & resource produc-tivity
End-of-life/ Disposal
Produc-tion
Product develop-ment and R&D
Supply chain manag-ement
Service
Value will be derived across the full ‘value chain’ Importance rankings from survey results
High Med Low
SOURCE: McKinsey survey of ~170 digital design and manufacturing leaders, DMDI
Value will be derived across the full ‘value chain’
3145
3932
3831
383536
29273030
18
4933
293524
2719
2119
23191412
4
-11-12
-17-23-20
-24-23-24
-27-26
-36-32
-40-37
-6-5
-10-7
-12-12-13
-17-12
-18-12-17
-13-35
Production (operations) Product design & development
Operations strategy & management
Production (capital productivity)
Human capital
Collaboration platform
Resource productivity & sustainability
Research & discovery
New "digital" business innovation
Service
Supply chain management
Sourcing
Risk management
End-of-life/disposal
Modest
ConsiderableLittle/no value
Significant
Product design, operations, capital productivity, R&D, and supply chain management were highlighted as areas of greatest value
“Where is the greatest value going to be derived along the value chain after implementation of digital manufacturing solutions?”
Successful digital leaders anchor their digital strategy back to clear sources of value
Revenue improvement
Cost reduction
Manufacturing & supply chain costs (labor, material, overhead, G&A)
Product quality
Delivery and service performance
Product innovation & customer satisfaction
Time to market
Revenue expansion of existing businessProfit
drivers
Higher capital utilization
Reduced equipment investment
Increased inventory turnover
Fixed capital
Working capital
Improved cash-to-cash cycle
Higher product availability/up-time
Improved asset utilization
For the processes and capabilities that drive each branch, measures of improvement include:
• Efficiency
• Effectiveness
• Speed
• Agility (ability to change for upside benefit or downside protection)
• Risk profile
“From a business metric perspective (e.g., cost, revenue), how important a driver can digital design & mfg be in creating value in each of these areas?”
Most critical
Very important
Important
Little/no importance
45
31
30
38
44
36
42
27
39
35
17
30
24
12
-17
-18
-27
-26
-15
-31
-23
-5
-7
-12
-5
-14
Cost (manufacturing, supply chain, capital)
Service levels
Time to market for new products
Product innovation
Product quality -4
Operations agility -4
Revenue expansion ofexisting business
Revenue & Growth drivers
Conventional cost and quality drivers
Digital is starting a paradigm shift: from operations as a cost & execution vehicle… to also an engine for innovation & growth
Organizations realize that technology creates no value…on its own
Capability Dimensions
Skills and structure to develop solution and extract value
Clear strategy, plan to drive competitive advantage
Information assets and associated management
Devices, apps and platforms to deliver Digital initiatives
Cascade strategy into a well-resourced plan, with aligned metrics & accountability
Example DMDII Projects bring together a collection of partners to solve a real problem, with tangible impact... “market pull” rather than “technology push”
Sample impactSample of potential applied research projects
Real-time shop floor advanced analytics
1
Intelligent machine ‘plug & play’ solution
2
Next-gen product & process design
3
Reduce rework and labor costs by up to 30%; $1MM over the life of the vehicle per hour saved in production
Reduce current 50% scrap rate by half
Reduce total system cost by 10-15%; accelerate time to market
• Team: Two top 5 US Defense companies, one leading European aerospace company, two Top 20 engineering schools
• Bring mobile computing and advanced analytics to shop floor decision-making, allowing real-time adjustments to complex vehicle system assembly
• Team: Two major global industrial conglomerates, industry-leading software company, two major manufacturing research universities
• Develop ‘plug & play’ hardware/software solution for adaptive machining
U̶ Allows machines to adjust based on unique shape of each cast/blank part
U̶ Interoperable across CNC machines
• Team: Major global aerospace company, Top 3 aeronautical engineering school, state-Federal research partnerships
• Design refresh of helicopter engine; 2 core innovationsU̶ Advanced analytics and modeling software: compare as designed, as made, as assembled, as serviced data
U̶ Collaboration software: real-time exchange & co-design
Sources of value from digital tech – voices of manufacturing leaders“What will be the most important drivers of future value from digital design and manufacturing?”
• “Next generation product design with ability to simultaneously model and optimize for:• Manufacturability and reliability• Affordability through lifecycle (including production
and maintenance post-sale)• Reduce design/purchasing risk by testing
technology earlier and cheaper”
• “Moving to a growth vs. cost story:• A new era post-commoditization with suppliers driving
to the next level of supplier collaboration• Move from cost-focus to:
• New product introduction focus• Speed to market focus
• Rapid prototyping and virtual testing”
• Connected customers with digitally enabled products, sharing data with manufacturers in real-time drives:• Proactive steps to address potential quality issues• Opportunities for new business models (e.g., selling
services)• Informs marketing of key trends to react to
• “Ability to change/improve agility:• Reduce non-value added change/rework• Execute value-add changes quickly• Allow for more experimentation• Proactive measurement/adaptability”
• “Big data definition/standards, new interoperable plat-forms, analytics, & best practice standards), to drive:• Production efficiency• Response time to customer feedback (from
years/months months/days)”
• “Ability to adapt to key system perturbations• Improved macro forecasting• Downtime reduction between product families• Respond to changes in customer preferences• Reduced design/manufacturing constraints”
• “Manufacturing feedback loops back to design:• Make-design link established• 3D design capability reducing cost in the make-design
link and improve quality• Product performance data feeds new product
innovation”
DMDII Facility to Open February 2015
