Smart Manufacturing: Advanced Sensing, Control and Platforms for Manufacturing

Transcription

1 Smart Manufacturing: Advanced Sensing, Control and Platforms for Manufacturing California-France Forum on Energy Efficiency Technologies 2014 Smart Manufacturing Leadership Coalition (SMLC) Jim Davis, Vice Provost IT & CTO, UCLA

2 Smart Manufacturing Smart Manufacturing, Data & Analytics Walk through illustrative examples and then generalize What is Smart? Generalize problem patterns and how we can think about them Technical and Business Drivers for Platform Infrastructure Map into architectural considerations of Advanced Sensing Control and Platform Technologies The Case for an Open Architecture Smart Manufacturing Platform Public Private Partnerships - Advanced Manufacturing Partnership 2.0 Recommendations

3 Machining Operation General Dynamics Scranton, PA

4 Holcroft Continous Roller Hearth

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6 General Dynamics Scranton Hot Forging Heat Treatment General Dynamics Scranton, PA

7 General Mills Networked-Based Manufacturing EDI transaction & quality certifications Business Systems, ERP Recipe Management Mapping formula into operating recipes Mapping SAP information Into operation Supply Chain Smart Grid Smart Factory Distribution Center Green Light Analyze - to put into production Make right ingredients confirmation on recipe Release meet requirements to release Customer FDA Tracking & traceability Graphics courtesy of Rockwell Automation

8 SMR High Fidelity Model Validation Evaluate new operating modes Web portal Specify parameters; submit workflow Sensors Octav e Reduced Order Model Collect data; validate model New temperature conditions Estimate time Check status Display results; validate New parameters; validate Update operations

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10 Smart Manufacturing s Commitment to a Comprehensive Approach Manufacturing Methods from Macro View

11 An Industry-Driven Open Architecture Shared Infrastructure Smart Manufacturing Information that drives the next century s structural shift in manufacturing. Smart Manufacturing Leadership Coalition (SMLC) 501c (6) Making real-time info available: when it is needed, where it is needed and in the form it is needed throughout the Manufacturing ecosystem SMLC Partnerships Test Beds - General Dynamics, General Electric, General Mills, General Motors, Praxair, Corning, Pfizer, NETL, Alcoa, Owens Corning, Advanced Manufacturing Partnership SoCal, Southwest Research Institute Design/Manufacturing Platform Providers JPL/NASA, UCLA, Rockwell, Honeywell, Emerson, Schneider Electric, Nimbis, OSISoft, Savigent Modeling & Simulation Materials, Design, Manufacturing Caltech/JPL, UCLA, UT Austin, Tulane, NCSU, CMU, Purdue Smart Manufacturing/Smart Grid EPRI Global Metrics/Outreach AIChE, ASQ, AMT, ACEEE, NCMS, MESA, MT Connect, Society of Manufacturing Engineers (SME), Sustainable Solutions, Spitzer & Boyes Agency partners DOE, NIST, NSF Regional Partners Center for Advanced Technology Systems/RPI, Wisconsin Manufacturing Institute, AMP SoCal, Association of State Energy Research & Technology Transfer Institutions (ASERTTI), National Association of State Energy Officials (NASEO)

12 What is SMART Test Bed Smart Systems Smart Machine Line Operations In-Production High Fidelity Modeling Dynamic Decisions Enterprise and Supply Chain Decisions Design, Planning and Model Development Integrated process machine and product management Benchmarking machine-product interactions Machine-power manage management Enhanced management complex behaviors Rapid qualification components products materials Integrated computational materials engineering (ICME) Performance management global integrated decisions Untapped enterprise degrees of freedom in efficiency, performance, and time Enterprise analytics and business operational tradeoff decisions Variability reduction In situ measurement and integrated value chains Tracking, traceability and genealogy Design models in production Product/material in-production ability New product, material technology insertion Adaptable machine configurations Configurable data and analyses for rapid analytics and model development External partner integration and interoperabilty

13 Technical and Business Drivers for Shared Infrastructure Achievable Meaningful Use Goals and Magnitude of Impact Demand-driven efficient use of resources and supplies in more highly optimized plants and supply 25% reduction in safety incidents 25% improvement in energy efficiency 10% improvement in overall operating efficiency 40% reduction in cycle times 40% reduction in water usage Product safety Product tracking and traceability throughout the supply Sustainable production processes for current and future critical industries 10x improvement in time to market in target industries 25% reduction in consumer packaging Process Intensification Maintain and grow existing U.S. industrial base Environment for broad innovation 25% revenue in adjacent industries 25% revenue in new products and services 2x current SME s addressing total market More highly skilled sustainable jobs created A Set of Issues Beyond Individual Company ROI constrained or prohibitive - Requires broader infrastructure investment to scale - Incremental investment difficult - Requires IT investment with 70% of cost non-value - Depends on other companies - supply chain - Need 80% reduction in cost of implementing modeling and simulation - 10x reduction in the cost of sensors and sensor infrastructure ROI opportunity comprehensive Multiple systems Integrated global performance metrics Aggregating data Installed base of serviceable manufacturing facilities $60 B in IT investment Retrofit Risk Major change & New business model Uncertain about technology, security & IP Organization IT capability lacking or IT not talking to operations Workforce skills Collaboration

14 Practitioner Adoptions Frost & Sullivan 2013 Survey of 347 Manufacturing CEOs 56% accelerate evaluation of transformative manufacturing technologies within 24 mos. Only 20% accept risks with early implementation ASQ 2014 Survey 700 Respondents 80% not knowledgeable of Smart Manufacturing 37% don t see a need; 29% cost barrier; 14% management resistance 20% knowledgeable 73% Great interest to do more 13% actually doing something 82% increased efficiency 49% fewer product defects 45% increased customer satisfaction 33% applied at plant level; 29% across all levels

15 Practitioner Market Challenges McKinsey Data US SME 19% of manufacturing sales & 13% of exports - 60% low to medium technology US SME s have languished in adopting technology - value add per employee relative to large companies 80% of large companies in 1960s 60% of large companies in 1990s

16 SMLC Industry-Academic-Government Platform Collaboration Model SMLC Industry-Driven Integrated Performance Metrics Micro, Meso, Macro Real-time Data & Modeling Workflow & Metric Toolkit/ App Development Key Development Resources Universities, SMM s Integrators, Labs Community Resources & Data Services UCLA Machine Product Management In Production High Fidelity Modeling Design and Planning Dynamic Decisions Enterprise & Supply Chain Decisions SM Platform Open-architecture Cloud-based Benchmarking Rapid Qualification Variability Management Real-time Plan Passes Performance Management Tracking, Traceability ICME Marketplace Composable Workflows Apps & Apps Toolkits & Toolkits Dept/SMM Small & Medium Enterprises Manufacturing Consortia Test Bed Manufacturer & Supplier Crosslinking Engagements Modeling & Interoperability Protocols IT Providers

17 Advanced Sensing, Control & Automation, Platform Modeling & Dynamic Orchestration of Manufacturing Intelligence in Heterogeneous Manufacturing Enterprises defined by SEAMs ASCPM SM Platform enabled virtual connection Seam Location where two or more parts of a manufacturing enterprise or supply chain are joined together System 1 System 2 Parts differ by time horizon, lexicon, technology, human in loop, culture, business drivers, vendors, or priorities. Interfaces

18 Design Data Smart Manufacturing: Multi-Layered Seams, Time, Data & Action Machines People - Materials Dynamic Manufacturing Ecosystem Prototype Materials & Process Tech Product Manufacturing Qualification In Service Control & Automation 10s control loops Time days 100s control loops Time -hours 1000s control loops Time - minutes Macro Layer Meso Layer Micro Layer Focus: 10x Multiple Pass Variability Reduction; Supply Chain Information Focus: 100x Event Variability/Tradeoff Adjustment; Dynamic Performance Mgmt.; Integrated Metrics Focus: Insertion, Qualification, ICME, High Fidelity Dynamic Operations Business Systems

19 Smart Manufacturing based on ISA 95

20 Smart Manufacturing & Vendor Products SM

21 Architect for Scalability, Cost, Extensibility, Entrée, Security & Multi Vendor Orchestrate function, data and time Compose heterogeneous environment workflows at User Level Provision secure IT on as needed basis No single scale time requirement in workflow Data to apps paradigm Separate Data & apps Data Partnership Workflow Orchestration Data collection, modeling & synchronization defined by workflow Smart Manufacturing Open Architecture Platform Composabilty Decision Market Place Design to manufacturing Workflow libraries Sensor Data Control & Automation Propriety Optimized Automation Workflows Data collection, modeling & Synchronization multi-scale time requirements embedded

22 SM Platform Architecture Data-based Workflow Orchestration Workflow (WfaaS) Provisioning Orchestration Tasking State Selectable Apps Proprietary Workflow Security Provenance Application Instances Provisioning

23 SM Platform Secure Data Interface and Workflow Architecture User & Role Authentication Browser and Remote Desktop Access Dash Boards UCLA/Nimbis Admin Visualization Workflows DOE Tesbed Marketplace SM Apps & Applications OEM 1 Commercial viewer(s) Visualize APP Metric APP Model Visualize Sensor Network Proprietary Platform DMZ service SM DMZ Https: SM Connect Platform Historian 1 O p e n D a t a OEM 1 Analysis BPM/Kepler Workflows Supplier 2 BPM/ Kepler Workflows Sensor Network Proprietary Platform DMZ server FTP to PI Platform Historian 2 M o d e l Supplier 2 DOE SM Cloud Platform

24 The Business Model of Data Big Data Practice Valuation Collective vs. Proprietary Manufacturing Health & Sustainability Collective Innovation & Practice The Business of Open Architecture Market, Valuation of Data & Innovation Collective Wisdom Converting Knowledge to Wisdom Open Architecture Data Valuation Collective vs. Proprietary IoT Smart Enterprise Manufacturing Smart Factory Manufacturing Data & Device Integration & Orchestration Secure Data Highways Smart Converting Information to Knowledge Converting Data to Information Secure I, P and SaaS

25 Performance Metrics with Platform Year 1 Year 2 Year 3 Year 4 Year 5 notes Decrease R & D cost/risk Accelerated pace of R & D outcomes Decrease in replication/deployme nt cost/risk & accelerated pace Retrofit modeling - waste heat minimization/energy productivity - base no advanced technology (See DOE proposal) 25% 30% 35% 40% 50% Compared to no platform baseline; 1 st year decrease - data & modeling infrastructure; 2 nd year progressive decrease - building on shared research 2 years to 1 year +5% faster +10% faster +15% faster 60% 1 2 replications 65% 1 year shift multiple replications 70% multiple replication s +20% faster 1 st year reduced duration - flexibility with modeling infrastructure; 2nd year progressive - more interface apps, better use standards, better modeling tools, consolidated experience 80% Multiple replications 1 year shift because R & D faster; Year 2 cost progression; consolidated experience, more interface apps, better standards, better modeling tools; pace accelerated multiple parallel replications 20% 30% 35% 40% 50% Advance control and low hanging fruit practices 20 25%; advanced real time Low 1 st phase energy 2 nd phase energy modeling & integration next 20%; hanging R & D R & D sophisticated integrated modeling next fruit Calculated for control and IT retrofits for existing process measurements, new, dynamic operating conditions; does not account for potential for new equipment Platform Energy Economics 25

26 What is Smart Manufacturing Internal & External Value Chain Networked-Based Manufacturing EDI transaction lot & quality certifications Business Systems, ERP Order adjustment Reduce premium shipments Tracking & traceability More customer freedom To customize Supply Chain Chain of custody Use Cases Mike Yost Mesa Smart Grid Smart Factory Distribution Center Customer Minimum just in case inventory & corrective actions thru entire system Configurable high fidelity/statistical modeling and analytics Dynamic plant configuration and readiness Dynamic product component/material configuration Faster changeovers & more variable order sizes Dynamic inventory minimization & management Graphics courtesy of Rockwell Automation

27 AMP 2.0 Recommendations

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