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The Smart Factory and the evolution towards Industry 4.0

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What steam has been the enabling technology for the 1st industrial revolution, electricity for the 2nd, and electronics for the 3rd, will IoT be for the 4th industrial revolution: The enabling technology to drive new levels of automation and data exchange in manufacturing. In such a hyper-connected world digital twin, supply chain transparency, and predictive maintenance are just some examples of productivity gains. In this session, Fujitsu experts will outline and discuss co-creation of industrial value networks and provide insights how Fujitsu is driving digital transformation in its own manufacturing plant.
Speaker: Christian Schregel
Frank Blaimberger

Published in: Technology
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The Smart Factory and the evolution towards Industry 4.0

  1. 1. 0 © 2017, Fujitsu EMEIA Fujitsu Forum 2017 #FujitsuForum
  2. 2. 1 © Copyright 2017 FUJITSU The Smart Factory and the evolution towards Industry 4.0 Christian Schregel Chief Evangelist Industry 4.0 Industry 4.0 Competence Center, CE Frank L. Blaimberger Head of Services & Tools A Division of Factory Operations
  3. 3. 2 © Copyright 2017 FUJITSU Industry 4.0 Competence Center
  4. 4. 3 © Copyright 2017 FUJITSU The path to Industry 4.0 Digital Transformation has high relevance for future business model Digital Transformation is high priority Executive Council topic Strategy is defined in detail, a roadmap is available Top-3 hurdles: • Lack of IT skills and resources (64%) • Lack of standards for M2M and IoT (57%) • Compliance regulations (53%) and High Security Demands (52%) The path towards the 4th industrial revolution is an evolutionary one Agree Disagree 0% 50% 100% Agree Disagree Source: IoT in German Manufacturing Industry, PAC GmbH on behalf of Fujitsu (n=160), 2017
  5. 5. 4 © Copyright 2017 FUJITSU Smart Business ModelsCross-Company Ecosystems Efficient Operations New Production Principles Data-driven Enhancements Horizontal Integration Partner Management Reduce to Max Fast IT ready Evolution of Fujitsu Smart Factory at Campus Augsburg
  6. 6. 5 © Copyright 2017 FUJITSU The Story So Far …. Easy Difficult Complex KaikakuKaizenWork Load 2000 2011 20191985 2016 Complicate WorkLoad
  7. 7. 6 © Copyright 2017 FUJITSU Areas of Smart Factory Based Solutions Digitalization and Transformation Worker‘s Place Assistance SystemsBridging Digital Gaps Technologies to support and enhance @ Shopfloor and Office
  8. 8. 7 © Copyright 2017 FUJITSU eInk @ Shopfloor  Substitution of Printing Materials  Printer,Paper Rols, Labels, Blades, etc.  Environmentalprotection (zero emission)  Dynamic Information Distribution  Last minute change ‘on the run’  Informationdistribution based on status  Display of Additional Content  Warnings, Changes, Instructions, etc.  Code Labels  Hidden control information
  9. 9. 8 © Copyright 2017 FUJITSU Smart Button @ Shopfloor  Digitally Integration of…  Legacy devices  Appliances w/o digital interfaces  Secured ‘black boxes’  Inexpensive goods  Non electrical productionrelated elements  Commodity Technology  Standard wireless technology WiFi 802.11xx  Low efforts of integrationinto corporateinfrastructure  Seamless integrationinto already existing supply data flow
  10. 10. 9 © Copyright 2017 FUJITSU Dynamic Test Control Process Control Test Controlling  Locked / Closed Q-Loops  Dynamic „Q-controlloops“  „Linestop“- Function Assembly & Soldering AOI & ICT Test  Intelligent, Dynamic Test Proceedings  Separation of test steps  Automatic controlling of test depth and test details
  11. 11. 10 © Copyright 2017 FUJITSU APS-Connect  Context Based Instruction Display  Multi-Use capability  Context based filtered / visualization  Smart Instruction Separation  Timing  Dynamic flow per single product  Automatic product recognition  Flexible material assignments  Interactions  Push services for support and materialsupply  Bi-directional information flow  Data Interface for Quality Tools APS: Worker’s Place Control Area
  12. 12. 11 © Copyright 2017 FUJITSU Dynamic Light @ Workbench  Need Based Driven  Content driven illumination assistance  Support for employees with special needs  Increase of ergonomicallyissues, based on product / configurationrelated operation  Economical  Power down after operation  Multi functional desk approach to reduce non functional space
  13. 13. 12 © Copyright 2017 FUJITSU Adaptive Testing  Event assistance  Dynamictest control  Problem visualization  Multiple operation / less invest Quality Improvement  Online problem solver  Process instruction  Escalation assessment  Trigger on event Predictive Maintenance  Improve OEE  Production stabilization  Resource allocation  Avoid unnecessary waste Operator Support  Context based Instruction  Quality increase  Agility and fast reaction Digital Supply Chain  Paperless Kitting: eInk  eKanban  Transparency along supply chain  “Pull” control Client Interface  Cloud based App  Seamless DataFlow towards customer  Data value for clients  Desk view load Shopfloor Management  Worker’splace control  Real time data  Mobile App Power / Energy Management  Peak reduction  Energy cost saving  Consumption supervision Current Smart Factory Readiness Level
  14. 14. 13 © Copyright 2017 FUJITSU Future Challenges …. Cost Sensitive Reduce to the Max Ready to change IT accounting schemes (e.g. pay per use) Fast IT ready Scalability and automation capability to decrease costs and expenditure Smart Industry 4.0 / IoT Ready To support and deploy new production principles and technologies Enhancements e.g. being ready for Smart Analytics / AI Comprehensive Partner-Management Embrace new partner and collaboration models Fujitsu’s Live UseCase Demonstrate manufacturing capability towards customers
  15. 15. 14 © Copyright 2017 FUJITSU Enabler for Cyber Physical Systems – Tool as a Service Request for Data Receive Value Fujitsu ‘Cyber Security’ Layer Factory Platform @ Fujitsu Cloud (K5) Data Regression Reconcile Smart Analytics & Prediction Smart Devices e.g. Sensor Grids IoT Apps Fujitsu Augsburg Customer Data Stream Supervision Monitor Fujitsu Gateway Appliance / Edge Computing Operation
  16. 16. 15 © Copyright 2017 FUJITSU Co-Creation Approach, e.g. Intelligent Dashboard Fujitsu Campus Augsburg Partner Requirements Customizing / Consulting Colmina @ K5 Smart Factory Fujitsu Global Product / Solution Portfolio Partner Co-Operation
  17. 17. 16 © Copyright 2017 FUJITSU Industry 4.0 Solution Stack Engineering Manufacturing Operation & Maintenance Process FacilityProduct Design Factory Design EnvironmentProduct Worker Consulting & Managed Security Services Collaborative Engineering Industrial Analytics Industrial-IoT & Edge Computing Fujitsu Industry 4.0 – Co-Create Industrial Value Networks Transparency, Interoperability and Innovation in internal and cross-organizational Value Chains Collaborative Engineering Product Lifecycle Management, based on transparent Value Chain Innovation Management Machine Utilization Quality Assurance Business Planning Product Design WIP Management Supply Chain Traceability MRO-Optimization Process Automation Demand Forecast Process Analytics Worker Assistant Solution Predictive Analytics Condition Monitoring Location Based Solutions Asset Tracking & TracingSolution Offerings
  18. 18. 17 © Copyright 2017 FUJITSU Process Automation Demand Forecast Process Analytics Worker Assistant Solution Predictive Analytics Condition Monitoring Location Based Solutions Asset Tracking & Tracing Process FacilityProduct Design Factory Design EnvironmentProduct Worker Consulting & Managed Security Services Engineering Cloud Orchestration Design & Simulation Tool Integration Design-Data Management Collaborative Engineering Fujitsu Industry 4.0 – Co-Create Industrial Value Networks Transparency, Interoperability and Innovation in internal and cross-organizational Value Chains Industrial Reporting Smart Analytics & Machine Learning Big Data IoT Platform Event Processing Platform Process Automation Platform RTLS / AIT Edge Computing UI-Applications Devices / Sensors / Tags / Beacons Industrial IoT Gateway PAN/ LAN / WAN / Mobile Product Lifecycle Management, based on transparent Value Chain Innovation Management Machine Utilization Quality Assurance Business Planning Product Design WIP Management Supply Chain Traceability MRO-Optimization Engineering Manufacturing Operation & Maintenance Industry 4.0 Solution Stack
  19. 19. 18 © Copyright 2017 FUJITSU Smart Quality Control with AI • Ultrasonic quality inspection generates massive amount of blade scanning data  Deep learning solution automates the scan data evaluation process  High gains in time efficiency by enabling skilled operators to focus on the important part of the data
  20. 20. 19 © Copyright 2017 FUJITSU Industry 4.0 Show Case K5 GER Sensor Data Access Dashboarding & Alerting Machine Sensor Data Motor current flow Data Dashboarding Alerting Predictive Data generation/Digital Twin • Native data from robot arm • Add. Sensors: • Temperature • Vibration gearing box (microphone) • Acceleration, Gyroscope via Smartphone Micro Services • IoT Data GW • Dashboarding and EPP • Data visualization on AR via table/HMD Data for animated Twin Customer Product Data Customer Product Analytics results on Twin Production Machine Analytics Services • Predictive Analytics • Dashboarding • AI Sound analyse including machine learning pattern definition (SWP)
  21. 21. 20 © 2017, Fujitsu EMEIA Industry 4.0 Competence Center Team Andreas Rohnfelder E-mail: andreas.rohnfelder@ts.fujitsu.com Head of Industry 4.0 CC Wieland Kordas E-mail: wieland.kordas@ts.fujitsu.com Christian Schregel E-mail: christian.schregel@tds.fujitsu.com Industry 4.0 Evangelist Leopold Sternberg E-mail: leopold.sternberg@ts.fujitsu.com Program Manager Collaborative Engineering Frank Zedler E-mail: frank.zedler@tds.fujitsu.com Program Manager Industrial-IoT & Edge Computing Program Manager Industrial Analytics
  22. 22. 21 © 2017, Fujitsu EMEIA

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