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The Contribution of Supply Chain Networks
Smart Manufacturing and Industrial IoT
Elemica Ignite
Sept 15th, 2015
Valentijn de Leeuw
Vice President
ARC Advisory Group
vdeleeuw@arcweb.com
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/
3
© ARC Advisory Group
Contents
1.  Smart Manufacturing for economic growth
2.  Key Initiatives SMLC, Industrie 4.0 and Horizon 2020
Innovator’s IIoT application examples
Their implications for supply chain networks
3.  New approaches to analytics
Supply Chain analytics
4.  Human-machine integration
The role of the Human in all this?
4
© ARC Advisory Group
Smart manufacturing: the growth strategy?
t  Manufacturing fuels the supply chain
t  Smart Manufacturing increases manufacturing
growth
5
© ARC Advisory Group
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
Impacted by Smart Manufacturing
6
© ARC Advisory Group
Smart Manufacturing Initiatives
Smart Manufacturing Leadership Coalition (US)
(High Value Manufacturing) Catapult (UK)
Industrial Internet Consortium (International)
Industrie 4.0 (Germany, Intl.)
Industrie du Futur (France)
Horizon 2020 (EU)
SPIRE (Sustainable process industries by Resource and Energy Efficiency
Factory of the Future
Alliance for IoT Innovation (EU)
Confederation of Indian Industries’ Smart Manufacturing (India)
Made in China 2025 (China)
Different visions for different outcomes
7
© ARC Advisory Group
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
8
© ARC Advisory Group
Copyrighted by ARC Advisory Group
t  Key Characteristics
•  Revitalize US manufacturing
since 2006, innovation
•  Oil and Gas, Process and
Hybrid focused
•  Engineering, Manufacturing
and Supply Chain
•  Private-public partnerships
•  Open SM platform, test
beds, market place
(standards)
•  Step-change improvements
•  Project cost and
duration
•  Efficiency, productivity,
cost reduction
•  Flexibilty and agility
•  Sustainability and safety
Smart Manufacturing Leadership Coalition
9
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Shorten SCM implementation time dramatically
t  SMLC Testbed
General Mills
t  Complex integrated
solution requirement
•  Each implementation
iteration takes years
•  Objective: reduce
application building
and integration to a
few months.
10
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Industrie 4.0
t  Key Characteristics
•  German > International
•  Rather discrete focused
•  PLM, Manufacturing and SC
•  Private-public partnerships
•  Technology / Approach
•  Digitalization
•  IT/OT/Process integration
•  Ubiquitous sensing / CPS
•  Big data – analytics
•  Stepchange or gradual change
•  Industry growth, biz
models
•  Project cost and duration
•  Efficiency, productivity,
cost reduction
•  Flexibilty and agility
•  Sustainability and safety
11
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Industrie 4.0t SupplyChain
Integration
• Intra-company
• Inter-company
• Interdisciplinary
12
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Traditional Supply Chaint AdaptiveProduction
• Demandpull
• Materialsupplycouldbe
providedviaSCON
Source: Poetter, Namur General Assembly 2013
13
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Industrie 4.0: Cyber-physical systemst VMIusingcyber-
physicalsystems
• Requiresreal-timeoperating
SCON!
Source:Poetter,NamurGeneralAssembly2013
14
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Increased throughput in existing plant
t  Industrie 4.0 at
ThyssenKrupp
t  Supply chain
integration
•  Thyssen-Krupp and
clients
•  Pull manufacturing
•  Throughput
increase
•  Avoid equipment/
surface size
increase
15
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Fine Chemicals and Life Sciences
Modular production technolgy
t Modularproduction
• EUco-sponsoredresearch
• 7F3Factorycasestudies
16
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Modular equipment, lines and production units
Revolution in engineering, construction and production
(Fine) Chemicals,
Polymers and
Pharmaceuticals
Modular reactor
Docking a modular plant
Details: “Advanced”
Manufacturing
17
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Future Implications of Modular/Mobile Production
t  Modularity of plants / exchangeable units
•  P&S must take all possible routings into account, also within
the plant and production lines
•  This is the “self-organizing” plant of Industrie 4.0
•  Plant size would not be a constraint anymore: line up/line
down
t  Mobile production lines
•  Production network becomes flexible
•  place the production unit where it creates maximum value/
minimum cost
18
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Other Smart Manufacturing Impacts
t  Digitization
•  Digital twin of the
plant enables fast
delocalization
t  Energy and feedstock
price volatility
•  Multi energy supply
•  Multi feedstock supply
t  Greening
•  Increasing use of
biological, living
materials
•  Biomass as feedstock
•  CO2-based feedstock
19
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Your Grandfather’s BI & Analytics…
Operational
Systems
(ERP, MES, SCM,
Financials etc.)
Data
Warehouse
12
6
39
1
2
5
4
7
8
10
11
20
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Add Velocity, Volume and Variety…
Operational
Systems,
M2M Data,
Partner
Data, Public
Data, Textual…
Data
Warehouse
12
6
39
1
2
5
4
7
8
10
11
21
© ARC Advisory Group
Copyrighted by ARC Advisory Group
…Has Too Much Latency for IIoT
Operational
Systems
(ERP, MES, SCM,
Financials etc.)
Data
Warehouse
Events Insight
22
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Cutting Latency
Operational
Systems,
M2M Data,
Partner
Data, Public
Data, Textual…
Data
Warehouse
1. Merged
Database
23
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Cutting Latency
2. Stream Processing (CEP)
3. Predictive Analytics
Operational
Systems
(ERP, MES, SCM,
Financials etc.)
Data
Warehouse
24
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Complex Event Processing
Complex Event Processing
(aka Event Streaming)
Real-Time
Automated
Decisions
Data Streams
25
© ARC Advisory Group
Copyrighted by ARC Advisory Group
What Predictive Analytics Isn’t…
3834
5117
6448
7908
9181
11497
10788
10021
8341
Dow Jones
Industrial Average
26
© ARC Advisory Group
Copyrighted by ARC Advisory Group
27
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Value from Variety (Unstructured Data)
Operational
Systems,
M2M Data,
Partner
Data, Public
Data, Textual…
Data
Warehouse
4. Text Analytics
28
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Unstructured Brings New Perspective
29
© ARC Advisory Group
Copyrighted by ARC Advisory Group
From MRPII to Advanced P&S
Collaborative
Forecasting
and
Demand
Management
Supply
&
Demand
Balancing
Scheduling
And
Capable to Promise
Rough Cut Capacity Planning
Distribution Requirements
Planning
Sales and Operations Planning
Master Production Scheduling
Material Requirements Planning
Infinite Capacity
Scheduling
Available to
Promise
Statistical
Forecastin
g
30
© ARC Advisory Group
Copyrighted by ARC Advisory Group
From MRPII to Advanced P&S and Analytics
Collaborative
Forecasting
and
Demand
Management
Supply
&
Demand
Balancing
Scheduling
And
Capable to Promise
Rough Cut Capacity Planning
Distribution Requirements
Planning
Sales and Operations Planning
Master Production Scheduling
Material Requirements Planning
Infinite Capacity
Scheduling
Available to
Promise
Statistical
Forecastin
g
Towards
Predictive
Supply Chain
Analytics and
Network
Optimization
31
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Emerging SM/IIoT Architecture – SC Analytics
Plant Operations
CorporatePurchasingEngineering
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
Client
3rd Parties
Supplier
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
32
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Analytics Levels and Methodologiest Level1:historicalreporting
• reporting
t Level2:PredictiveAnalytics
• Forecasting
t Level3:Prescriptiveanalytics
• Recommendations,optimization
Tim Sharpe, Energy management at Sabic UK, Sabisu, EIF 2015
33
© ARC Advisory Group
Copyrighted by ARC Advisory Group
t  Negotiation, collaborative forecasts, engaged social
networking, motivation, decision making …
We continue to need unique human skills
34
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Human-Machine Integration
t  Human
•  Provide data to the system
•  Need to develop trust
•  Assesses, delegates,
interprets, judges and
decides with consciousness
and skill
Cognitive agents
unload the human
Semantic interaction:
meaningful human-
system communication
Source: Maurice Wilkins, Valentijn de Leeuw
t  Machine
•  Allows focusing on problem
solving and decision making
•  Provide context
•  Ecological interface design
Predictive analytics
proposes actions
Acts ethically and with
compassion
35
© ARC Advisory Group
Copyrighted by ARC Advisory Group
Implementation Strategies
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
dwhite@arcweb.com
@addicted2data
IIoT Newsletter:
http://industrial-iot.com/
subscribe-to-newsletter/
Thanks to David for the analysis and survey
on IIoT, big data and analytics

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IGNITE 2015 Valentijn de Leeuw - Industry 4.0: The industrial Internet of Things

  • 1. The Contribution of Supply Chain Networks Smart Manufacturing and Industrial IoT Elemica Ignite Sept 15th, 2015 Valentijn de Leeuw Vice President ARC Advisory Group vdeleeuw@arcweb.com
  • 2. 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/
  • 3. 3 © ARC Advisory Group Contents 1.  Smart Manufacturing for economic growth 2.  Key Initiatives SMLC, Industrie 4.0 and Horizon 2020 Innovator’s IIoT application examples Their implications for supply chain networks 3.  New approaches to analytics Supply Chain analytics 4.  Human-machine integration The role of the Human in all this?
  • 4. 4 © ARC Advisory Group Smart manufacturing: the growth strategy? t  Manufacturing fuels the supply chain t  Smart Manufacturing increases manufacturing growth
  • 5. 5 © ARC Advisory Group 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 Impacted by Smart Manufacturing
  • 6. 6 © ARC Advisory Group Smart Manufacturing Initiatives Smart Manufacturing Leadership Coalition (US) (High Value Manufacturing) Catapult (UK) Industrial Internet Consortium (International) Industrie 4.0 (Germany, Intl.) Industrie du Futur (France) Horizon 2020 (EU) SPIRE (Sustainable process industries by Resource and Energy Efficiency Factory of the Future Alliance for IoT Innovation (EU) Confederation of Indian Industries’ Smart Manufacturing (India) Made in China 2025 (China) Different visions for different outcomes
  • 7. 7 © ARC Advisory Group 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
  • 8. 8 © ARC Advisory Group Copyrighted by ARC Advisory Group t  Key Characteristics •  Revitalize US manufacturing since 2006, innovation •  Oil and Gas, Process and Hybrid focused •  Engineering, Manufacturing and Supply Chain •  Private-public partnerships •  Open SM platform, test beds, market place (standards) •  Step-change improvements •  Project cost and duration •  Efficiency, productivity, cost reduction •  Flexibilty and agility •  Sustainability and safety Smart Manufacturing Leadership Coalition
  • 9. 9 © ARC Advisory Group Copyrighted by ARC Advisory Group Shorten SCM implementation time dramatically t  SMLC Testbed General Mills t  Complex integrated solution requirement •  Each implementation iteration takes years •  Objective: reduce application building and integration to a few months.
  • 10. 10 © ARC Advisory Group Copyrighted by ARC Advisory Group Industrie 4.0 t  Key Characteristics •  German > International •  Rather discrete focused •  PLM, Manufacturing and SC •  Private-public partnerships •  Technology / Approach •  Digitalization •  IT/OT/Process integration •  Ubiquitous sensing / CPS •  Big data – analytics •  Stepchange or gradual change •  Industry growth, biz models •  Project cost and duration •  Efficiency, productivity, cost reduction •  Flexibilty and agility •  Sustainability and safety
  • 11. 11 © ARC Advisory Group Copyrighted by ARC Advisory Group Industrie 4.0t SupplyChain Integration • Intra-company • Inter-company • Interdisciplinary
  • 12. 12 © ARC Advisory Group Copyrighted by ARC Advisory Group Traditional Supply Chaint AdaptiveProduction • Demandpull • Materialsupplycouldbe providedviaSCON Source: Poetter, Namur General Assembly 2013
  • 13. 13 © ARC Advisory Group Copyrighted by ARC Advisory Group Industrie 4.0: Cyber-physical systemst VMIusingcyber- physicalsystems • Requiresreal-timeoperating SCON! Source:Poetter,NamurGeneralAssembly2013
  • 14. 14 © ARC Advisory Group Copyrighted by ARC Advisory Group Increased throughput in existing plant t  Industrie 4.0 at ThyssenKrupp t  Supply chain integration •  Thyssen-Krupp and clients •  Pull manufacturing •  Throughput increase •  Avoid equipment/ surface size increase
  • 15. 15 © ARC Advisory Group Copyrighted by ARC Advisory Group Fine Chemicals and Life Sciences Modular production technolgy t Modularproduction • EUco-sponsoredresearch • 7F3Factorycasestudies
  • 16. 16 © ARC Advisory Group Copyrighted by ARC Advisory Group Modular equipment, lines and production units Revolution in engineering, construction and production (Fine) Chemicals, Polymers and Pharmaceuticals Modular reactor Docking a modular plant Details: “Advanced” Manufacturing
  • 17. 17 © ARC Advisory Group Copyrighted by ARC Advisory Group Future Implications of Modular/Mobile Production t  Modularity of plants / exchangeable units •  P&S must take all possible routings into account, also within the plant and production lines •  This is the “self-organizing” plant of Industrie 4.0 •  Plant size would not be a constraint anymore: line up/line down t  Mobile production lines •  Production network becomes flexible •  place the production unit where it creates maximum value/ minimum cost
  • 18. 18 © ARC Advisory Group Copyrighted by ARC Advisory Group Other Smart Manufacturing Impacts t  Digitization •  Digital twin of the plant enables fast delocalization t  Energy and feedstock price volatility •  Multi energy supply •  Multi feedstock supply t  Greening •  Increasing use of biological, living materials •  Biomass as feedstock •  CO2-based feedstock
  • 19. 19 © ARC Advisory Group Copyrighted by ARC Advisory Group Your Grandfather’s BI & Analytics… Operational Systems (ERP, MES, SCM, Financials etc.) Data Warehouse 12 6 39 1 2 5 4 7 8 10 11
  • 20. 20 © ARC Advisory Group Copyrighted by ARC Advisory Group Add Velocity, Volume and Variety… Operational Systems, M2M Data, Partner Data, Public Data, Textual… Data Warehouse 12 6 39 1 2 5 4 7 8 10 11
  • 21. 21 © ARC Advisory Group Copyrighted by ARC Advisory Group …Has Too Much Latency for IIoT Operational Systems (ERP, MES, SCM, Financials etc.) Data Warehouse Events Insight
  • 22. 22 © ARC Advisory Group Copyrighted by ARC Advisory Group Cutting Latency Operational Systems, M2M Data, Partner Data, Public Data, Textual… Data Warehouse 1. Merged Database
  • 23. 23 © ARC Advisory Group Copyrighted by ARC Advisory Group Cutting Latency 2. Stream Processing (CEP) 3. Predictive Analytics Operational Systems (ERP, MES, SCM, Financials etc.) Data Warehouse
  • 24. 24 © ARC Advisory Group Copyrighted by ARC Advisory Group Complex Event Processing Complex Event Processing (aka Event Streaming) Real-Time Automated Decisions Data Streams
  • 25. 25 © ARC Advisory Group Copyrighted by ARC Advisory Group What Predictive Analytics Isn’t… 3834 5117 6448 7908 9181 11497 10788 10021 8341 Dow Jones Industrial Average
  • 26. 26 © ARC Advisory Group Copyrighted by ARC Advisory Group
  • 27. 27 © ARC Advisory Group Copyrighted by ARC Advisory Group Value from Variety (Unstructured Data) Operational Systems, M2M Data, Partner Data, Public Data, Textual… Data Warehouse 4. Text Analytics
  • 28. 28 © ARC Advisory Group Copyrighted by ARC Advisory Group Unstructured Brings New Perspective
  • 29. 29 © ARC Advisory Group Copyrighted by ARC Advisory Group From MRPII to Advanced P&S Collaborative Forecasting and Demand Management Supply & Demand Balancing Scheduling And Capable to Promise Rough Cut Capacity Planning Distribution Requirements Planning Sales and Operations Planning Master Production Scheduling Material Requirements Planning Infinite Capacity Scheduling Available to Promise Statistical Forecastin g
  • 30. 30 © ARC Advisory Group Copyrighted by ARC Advisory Group From MRPII to Advanced P&S and Analytics Collaborative Forecasting and Demand Management Supply & Demand Balancing Scheduling And Capable to Promise Rough Cut Capacity Planning Distribution Requirements Planning Sales and Operations Planning Master Production Scheduling Material Requirements Planning Infinite Capacity Scheduling Available to Promise Statistical Forecastin g Towards Predictive Supply Chain Analytics and Network Optimization
  • 31. 31 © ARC Advisory Group Copyrighted by ARC Advisory Group Emerging SM/IIoT Architecture – SC Analytics Plant Operations CorporatePurchasingEngineering 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 Client 3rd Parties Supplier 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
  • 32. 32 © ARC Advisory Group Copyrighted by ARC Advisory Group Analytics Levels and Methodologiest Level1:historicalreporting • reporting t Level2:PredictiveAnalytics • Forecasting t Level3:Prescriptiveanalytics • Recommendations,optimization Tim Sharpe, Energy management at Sabic UK, Sabisu, EIF 2015
  • 33. 33 © ARC Advisory Group Copyrighted by ARC Advisory Group t  Negotiation, collaborative forecasts, engaged social networking, motivation, decision making … We continue to need unique human skills
  • 34. 34 © ARC Advisory Group Copyrighted by ARC Advisory Group Human-Machine Integration t  Human •  Provide data to the system •  Need to develop trust •  Assesses, delegates, interprets, judges and decides with consciousness and skill Cognitive agents unload the human Semantic interaction: meaningful human- system communication Source: Maurice Wilkins, Valentijn de Leeuw t  Machine •  Allows focusing on problem solving and decision making •  Provide context •  Ecological interface design Predictive analytics proposes actions Acts ethically and with compassion
  • 35. 35 © ARC Advisory Group Copyrighted by ARC Advisory Group Implementation Strategies 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
  • 36. Acknowledgement David White Senior Analyst ARC Advisory Group dwhite@arcweb.com @addicted2data IIoT Newsletter: http://industrial-iot.com/ subscribe-to-newsletter/ Thanks to David for the analysis and survey on IIoT, big data and analytics