internet of things cologne 2015: the contribution of new data storage and analytics strategies to...

The Contribution of New Data Storage and Analytics Strategies to Smart Manufacturing

and Economic Growth

Internet of Things Cologne with inmation Sept 10th, 2015

Valentijn de Leeuw Vice President

ARC Advisory Group [email protected]

2 © ARC Advisory Group

What ARC Does

t  ARC helps Suppliers •  Accelerate Revenue Growth & Manage Costs •  Bring Products & Services to Market Faster and more

Effectively t  ARC helps Industrial Companies

• Understand the Value of Emerging Technologies •  Choose Appropriate Suppliers for their Unique Needs •  Implement Operational Best Practices

Blog: Newsletter: http://industrial-iot.com http://industrial-iot.com/subscribe-to-newsletter/


Contents

1.   Why do we need Innovation (and Industrial IoT) 2.   New approach to Industrial Big Data (Analytics) 3.   Where does industry stand 4.   Innovator’s IIoT application examples 5.   How to get started


vo•cab•u•la•ry (vō-kăbˈyə-lĕrˌē)

t  Smart Manufacturing • Advanced Manufacturing

• …

• Smart Manufacturing Technologies • Industrial Internet of Things (IIoT) • …

t  Smart Manufacturing Initiatives


Smart manufacturing: the right strategy?

t  Getting lost in initiatives and technologies? •  Defining, distinguishing and mapping? •  Missing the boat?

The question is do we pursue the right strategy? •  Which innovation impacts manufacturing growth most? •  What to focus on? •  Quick wins? Short payback?

t  Time to ZOOM OUT and REFOCUS


Manufacturing growth and competitiveness

Manufacturing Resilience Competitiveness Growth

High degree of Technology intensity Technology/manufacturing complexity Quality

DE

Complexity index 2010 versus 1995

SE UK

FR IT

ES

Picture: Airbus SAS S. Ramadier


Manufacturing and R&D / Innovation

t  We need innovation … •  Product innovation •  Process innovation •  Productivity innovation

t  … and … •  Lift technology content, complexity and quality •  Create positive price and demand effects

t  … for manufacturing … •  Competitiveness •  Output growth •  Downturn resilience


1b Data Points

Unmodified Picture from https://en.wikipedia.org/wiki/Petrochemical under license CC BY 3.0 (freely reusable)


Industrial Data Is

Big Data


Your Grandfather’s BI & Analytics…

Operational Systems

(ERP, MES, SCM, Financials etc.)

Data Warehouse

12

6

3 9

1 2

5 4

7 8

10 11


Add Velocity, Volume and Variety…

Operational Systems,

M2M Data, Partner

Data, Public Data, Textual…

Data Warehouse

12

6

3 9

1 2

5 4

7 8

10 11


…Has Too Much Latency for IIoT

Operational Systems


Data Warehouse

Events Insight


Cutting Latency


M2M Data, Partner


Data Warehouse

1. Merged Database


Cutting Latency

2. Stream Processing (CEP) 3. Predictive Analytics

Operational Systems


Data Warehouse


What Predictive Analytics Isn’t…

3834

5117

6448

7908

9181

11497 10788

10021

8341

Dow Jones Industrial Average


Value from Variety (Unstructured Data)


M2M Data, Partner


Data Warehouse

4. Text Analytics


Unstructured Brings New Perspective


The Cloud

t  Industrial Data Analytics • Smart manufacturing technology

t  In the Cloud • Industrial IoT application


Is Industry Using Big Data…?

3% “Big Data is

Irrelevant for Us”



16% “Projects Live, or Near Live”



38% “Don’t Understand

Big Data or Why it Matters”


Copyrighted by ARC Advisory Group

Hybrid Architecture Emerging

Plant Operations

Corporate Purchasing Engineering

XYZ Chemical XYZ Chemical XYZ Chemical

Enterprise

Maintenance

XYZ Chemical

Device buses

Production Management

Logic & Motion

Discrete ControlProcess Control

Infrastructure (Networks…)

Wireless

HMI / Workstations

Fieldbus

Application Specific

Appliances

Safety

XYZ Chemical

Machine Mfr.

3rd Parties

Service Provider

Physical asset with sensors, actuators

Local IoT Compute and Communicate module

Smart Machine

IoT Smart Module

Emerging Option: Connect Assets Using New Technologies

New IoT Analytics and Applications

Purdue Hierarchy

IIoT Hierarchy

Enterprise



IoT at Intel: asset, production & quality analytics

http://www.intel.com/content/www/us/en/internet-of-things/white-papers/industrial-optimizing-manufacturing-with-iot-paper.html

t  IoT solution as add-on on top of MES

t  Case 1: predictive asset analytics 9M$ •  Reduce non-genuine off-

spec (losses -25%) •  Predictive maintenance

(spare cost -20%) t  Case 2: Reduce yield losses

of soldering process t  Case 3: Image analytics for

conformity testing



Major benefits using process analytics at SABIC UK

Tim Sharpe, Energy management at Sabic UK, Sabisu, EIF 2015 t 

Clo

ud

-bas

ed A

nal

ytic

s at

S

AB

IC U

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• $1

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ben

efits

at

leve

l 4

• $2

7 m

ben

efits

leve

l 3

• $1

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efits

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• Pa

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Manufacturing Analytics at Dow

t  Culture change t  Plant

performance improvement

t  From post-mortem analysis to preventive action

t  Next: roll-out

Source: Lloyd Colegrove, Dow Chemicals, ARC’s European Industrie Forum 2015



Example: North Sea Oil Rig t  Problem

•  Lost production from unplanned downtime

t  Solution •  Predict component failure in

advance t  How

•  Predictive Analytics •  Cloud •  Outsourced monitoring

t  Benefit •  $7.5m revenue saved thru timely

change of water pump seal © Richard Child



Refocus and get going

t  Target radical efficiency improvements •  Start small

t  Choose areas of innovation in line with business strategy and sector needs •  Per production type, process or plant type

t  Set goals, define KPI’s •  Improve product, material, substance performance if possible •  Innovate business models (e.g. circular) and value creation ecosystem •  Sustainability

t  Assessment methodology and Roadmap •  Maturity model, business case, roadmap •  Feasible roadmap, with regular updates

Acknowledgement

David White Senior Analyst ARC Advisory Group [email protected] @addicted2data

IIoT Newsletter: http://industrial-iot.com/subscribe-to-newsletter/

Thanks to David for the analysis and survey on IIoT, big data and analytics