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

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Valentijn de Leeuw, VP at ARC Advisory Group, presents an overview of the major IIoT-related trends, global initiatives, related technologies and more for better understanding how the IIoT fits into supply chain strategies and what benefits companies can derive from this next generation of manufacturing initiatives.

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

  1. 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. 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. 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. 4 © ARC Advisory Group Smart manufacturing: the growth strategy? t  Manufacturing fuels the supply chain t  Smart Manufacturing increases manufacturing growth
  5. 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. 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. 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. 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. 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. 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. 11 © ARC Advisory Group Copyrighted by ARC Advisory Group Industrie 4.0t SupplyChain Integration • Intra-company • Inter-company • Interdisciplinary
  12. 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. 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. 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. 15 © ARC Advisory Group Copyrighted by ARC Advisory Group Fine Chemicals and Life Sciences Modular production technolgy t Modularproduction • EUco-sponsoredresearch • 7F3Factorycasestudies
  16. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 26 © ARC Advisory Group Copyrighted by ARC Advisory Group
  27. 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. 28 © ARC Advisory Group Copyrighted by ARC Advisory Group Unstructured Brings New Perspective
  29. 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. 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. 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. 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. 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. 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. 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. 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

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