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Smart Manufacturing - Working Group Breakout 10/3/2017

This working group meeting aims to review the collaborative framework for smart manufacturing, rank IIoT application segments, identify issues in technology levels, and explore opportunities for collaborative development projects.

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Smart Manufacturing - Working Group Breakout 10/3/2017

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  1. Smart Manufacturing - Working Group Breakout 10/3/2017

  2. Identify the Make-up of the Room • IIoT Seekers • IIoT Solvers • Application Level • Systems Level • Communications Level • Smart Device/Systems Level • Cyber Security Levels • Workforce Training and Skills Development Level

  3. Working Group Meeting Review - Objectives • Review the Smart Manufacturing Collaborative Framework; • Rank IIoT Application Segments by importance; • Identify issues to be addressed in the 5 Technology Levels; • Identify opportunities for collaborative development projects.

  4. Working Group Meeting Attendees • Gary Klinger, President, Virtual Intelligent Analytics • Bob Eckman - Chief Information Security Officer, MCPc • Gautam Bagal - Electrical Sector, Engineering Team, Eaton • Hugh Ariff - Director, Technical Strategy and Chief Architect Signature Client Group- Midwest, AT&T • Peter Buca - Vice President, Technology & Innovation, Parker Hannifin • Bill Butcher – Information Solutions Division, Enterprise Architect, Lubrizol • Tony Crimaldi - Senior Director Marketing & Technology, Avantia • Marvin Davis - Global ABS Director, Arconic

  5. IoT – A Framework for Us to Use

  6. Engaging a Wide Breadth of Disciplines

  7. Framework Used to Address IIoT for the Region • Seeker defines their needs (assisted by Team NEO and regional partners) • Solver’s capabilities are captured in a database (companies/institutions with expertise in each of the 5 technology levels) • The Seeker profile is compared to the database of Solvers and a Cluster team is identified

  8. Smart Manufacturing: Using IIoT toDefine Application Segments of Focus Team NEO has interviewed industry participants in NEOhio and at industry forums. Primary areas of interest: • Supply Chain Management • Operating Efficiency • Product Quality • Predictive Maintenance • Inventory Control • Occupational Safety Rick will present details on findings in each application area. Smart Manufacturing

  9. Scope Based on IoT Structure

  10. Lubrizol Capabilities and Architecture

  11. Sample of project data base tool

  12. Predictive Maintenance (31) • Monitor mechanical, electrical, chemical and physical parameters of machines/processes – include vision and infrared sensors; • Mine history data from machine to identify trends for potential failure. Use artificial intelligence to identify anomalies that indicate potential failure; • Use machine learning to reduce opportunity for defective parts and final product. From WG meeting: • Equipment Health • Equipment health drivers • Productivity • Impact of sensor implementation – role of sensor reliability

  13. Operating Efficiency (30) • Place sensors and intelligence on every piece of production equipment; • Process modeling and real-time optimization; • Implement standard sensor and intelligence into new machines and legacy machines; • Monitor, analyze and adjust in real-time, influences on production like energy consumption and quality. From WG meeting: • Asset utilization • Selection from fill stack • System selection and value • Value creation • Complexity and variation • Arconic – ROI on sensor implementation

  14. Supply Chain Management (20) • track the physical status of goods, the management of materials, and financial information involving all parties; • improve the time-to-market of products, reduce costs, and allow all parties in the supply chain to better manage current resources and plan for future needs; • advanced algorithms to determine the best way to fill an order. From WG meeting: • Include outbound and inbound • Warehousing, logistics • Inventory control

  15. Other • IT – prioritize innovation vs support • Go after low hanging fruit • Solution fragmented • Complex mix of answers • Some independents offer solutions but don’t have access to full solutions • Analytics is highest value (even in market analysis) • Catalog value solutions for mfgs – ROI • Data retention recycling • Enablement • Data integration across applications • Innovation

  16. From Separate Conversations During Break • Separate data information from control information; • Complexity of applications varies across a spectrum – one size does not fit all; • Need a folder of case studies and lessons learned; • Different challenges for legacy shop floor implementation as compare to new or expansion; • Collaborative Team must include a “face-to-the-customer” leader; • A cross cutting (application segments) cybersecurity strategy and implementation plan needs to be developed/assimilated.

  17. Open Discussion • Validate identified issues; • Identify any outstanding issues for the selected application segments; • What will the collaborative teams consist of?

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