The infusion of intelligence that transforms the way industries conceptualize, design and operate the manufacturing enterprise.

Smart Manufacturing as a Real-Time Networked Information Enterprise

Jim Davis UCLA/Institute for Digital Research and Education and Tom Edgar UT Austin SMLC (501c6)

https://smartmanufacturingcoalition.org http://smartmanufacturing.com What is Smart Manufacturing?

Smart Manufacturing enables all information about the manufacturing process to be available when it is needed, where it is needed, and in the form that it is needed across entire manufacturing supply chains, complete product lifecycles, multiple industries, and small, medium and large enterprises. Technology Roadmap Report (2009)

1. Motivating Smart Process Manufacturing

2. The Business Case and the Business Transformation

3. The Technical Transformation

4. The Smart Process Manufacturing Roadmap

5. The Path Forward

3 Implementing 21st Century SM Report (2011)

Priority actions in four categories:

• Industrial Community Modeling and Simulation Platforms for Smart Manufacturing

• Affordable Industrial Data Collection and Management Systems

• Enterprise Wide Integration: Business Systems, Manufacturing Plants and Suppliers

• Education and Training in Smart Manufacturing

4 SMLC Program Agenda for a Smart Manufacturing Platform  Lower the cost for applying advanced data analysis, modeling, and simulation in core manufacturing processes

 Build pre-competitive infrastructure including network and information technology, interoperability, and shared business data

 Establish an industry-shared, community-source platform and associated software that functions as an “apps” store and clearinghouse

 Create and provide broad access to next-generation sensors, including low- cost sensing and sensor fusion technologies

 Establish test beds for smart manufacturing concepts and make them available to companies of all sizes

Industrial Gas Manufacturing

Steel

Energy

Bio/Pharma

Electronics

Healthcare Customers Energy Supply Production and Delivery

Our customers demand capital discipline and high reliability Our goal is to meet their demands and maintain high energy efficiency Smart Manufacturing Helps Meet Our Goals

• Low cost sensors and wireless enable real time decisions

• Hosted computing improves results at a lower cost Design Operations

• Common infrastructure facilitates supply chain collaboration

Machine Operations & Line Management Trade-Offs General Dynamics

Machine Function Benchmarking & Integrated Line and Energy Management

Managing Power from the Grid FORD In-Production Virtual Aluminum Castings Target Strength = 220 MPa 210 230

Aging at 250C for 3hrs 220

Aging temperature 240C for 5hrs

Initial Heat Treatment Process 205

Optimized Heat Treatment Process John Allison AIChE 2010 Faster and Stronger !! General Mills Farming • Customers “pushing” demands • Tracking & Traceability Supply Chain

Manufacturing Plant

Distributor

Customer General Mills Networked-Based Manufacturing Intelligence & Collaborative Manufacturing EDI transaction Recipe Management & quality Mapping formula into operating certifications recipes Business Systems, ERP Mapping SAP information Into operation

Customer Supply Chain Distribution Center Smart Factory FDA Tracking & traceability Green Light Smart Grid Analyze - to put into production Make – right ingredients – confirmation on recipe

11 Release – meet requirements to release GM’s ECO System of “ STUFF”

Demand Driven Supply Chain Value Creation Green Light Green Light Optimized to Convert to Ship Inventory Allergen/Micro WorkFlow eCOA Business Applications Supplier Managed Inv Line Supply Bin Mgmt Overusage Trace/Recall BOM Validation Yard Mgmt Directed Work

Plan

Core Functions Mat’l Direct Order Engine History Inventory Inventory Inventory Raw WorkFlow Plant Floor Production Production Production Production LotTracking Optimization Consumption Line Schedule Line Demand Finished Product Finished Master Data (BOM,Specs,Vendor,Ingredients,FP) Core Systems MQIS MES SAP ERP SAP MRP SAP APO SAP PLM Red Prairie

Data Input Test Bed Generated SM Systems

Smart Machine Operations • In production machine-product management • Benchmarking machine-product interactions • Integrated dynamic management of machine-electrical power interactions • Adaptable machine configurations

In Production Use of High Fidelity Modeling and Simulation • High fidelity modeling for better management • Rapid qualification of components and products

In Production Decision Making with Global Integrated Metrics • Dynamic Business and Operational Tradeoff Decision-Making • Dynamic performance management of global integrated metrics • Untapped cross factory degrees of freedom for optimizing efficiency and performance and compressing time

Supply Chain Management • Supply chain variability reduction and management of risk • Tracking and traceability Industry Test Bed Strategy Industry-Driven Defined from Test Bed systems The Technical Basis for Collaborative Manufacturing and the SM Platform

Meta 1 Challenge 1 Challenge 2 Integrated Workforce, Factory and supply chain demonstrations Integration of manufacturing enterprise data, sites of applied manufacturing intelligence Cyber, Physical System control, automation, management and Performance optimization infrastructures Variability Reduction Benchmarking

Meta 3 Meta 2 Multi-Dimensional Smart Higher Fidelity Production Demand-Dynamic Real-time Qualification Manufacturing Customer to Source Integrated Computational Variability Planning Materials Engineering Materials & Energy Mgmt.

Challenge 3 Challenge 4 META 4 Precompetitive and competitive Real-time syncing virtual models and Interoperable Supply Chain physical operations community source modeling innovation & Network simulation assimilation platform Control, Automation,

Optimization Management & Decision

Enabling New & Dormant Technologies First Concept of the Smart Manufacturing Platform Infrastructure for Real-Time Data Driven Modeling and Simulation SMLC Industry-Driven SMEs Integrated Small & Medium Performance Variability Enterprises Metrics Management Manufacturing Micro, Meso, Macro Real-time Plan Consortia Passes

Real-time Data & Apps Test Bed Community Pre-competitive Store Manufacturer Modeling Workflow To& Source & Competitive Cloud & Supplier & Metric Toolkit/ Resources Hub Crosslinking Services Engagements App Development UCLA Benchmarking Rapid Key Standards and Development Qualification ICME Reference Resources Architecture Universities, SME’s IT Providers Manufacturers, Labs Community Source Market Place

Real Time Virtual Manufacturing Demonstration Facility (VMDF) 17 11/1/11 SMLC Partners & Collaboration Roles

Test Beds - General Dynamics, General Mills, General Motors, Praxair, Corning, Pfizer, Alcoa, Exxon Mobil, Shell, Air Liquide, RPI/Center for Advanced Technology Systems Design/manufacturing Platform Providers – JPL/NASA, UCLA, Rockwell, Honeywell, Emerson, Nimbis Modeling & Simulation Materials, Design, Manufacturing – Caltech/JPL, NETL, Argonne, UCLA, UT Austin, Tulane, NCSU, CMU, Penn, Purdue Smart Manufacturing/Smart Grid – EPRI Global Performance Metrics – AIChE, ACEEE, Sustainable Solutions Agency partners – NIST, NSF Regional partners - Center for Smart Manufacturing (CA), Wisconsin Manufacturing Institute Multi-Layer Smart Manufacturing (MLSM) Workflow Foundation

Design Materials & Product In Prototype Qualification Data Process Tech Manufacturing Service

Macro Layer People Involved • Product Volume Integrated Metrics & • Scheduling • Supply Chain Decision Making

APP Store Meso Layer Virtual • Reference Flows • Management MDSM • Process Models • Machine Flow Host Control • Optimization • • Dash Board •Metrics •Collaboration

Micro Layer Conditional decisions • Sensors/Actuators MDSM Program • Control/Optimization Model building &updates • Automation “Host” Manufacturing Model insertion Initiatives Workflow Distinguished from Control & Automation

General Process Machine & Line Benchmark Dynamics Data Data Benchmarking Factory Data Control Automation Model Factory Workflow

Workflow Service Framework

Process & Line Check Table Calculate Dashboard Set Point Optimal Machine Machine, Energy, Recommend Conditions Usage Product Metric Tradeoff Points

Computational Batch Scheduler Resources

New Machine Run Machine Update Machine Build Table Table Model Maintenance Usage Pattern- Optimal Machine Usage Model Accepted Process Data Based Analyzer Usage Windows Multi-Layered Smart Manufacturing Management (MLSMM) Time Managed as Workflow Not Control Transformational Machines – People - Materials Dynamic Manufacturing Ecosystem

Materials & Product In Design Prototype Qualification Service Data Process Tech Manufacturing Macro Layer Current Practice – One 10s of control loops Pass per Day per Control Points - ? Event; Too Late, Stale Manpower - X Data, Slow Responsive Time – days Manufacturing

Meso Layer Goals: 100x Event 100s of control loops Variability Adjustment Control Points - ? Capability & Dynamic Manpower – 10X Certification Time -hours Improvement

Focus: Integrated 1000s of control loops Micro Layer metrics, Qualification, Control points - Computational Manpower – 100X Materials Engineering, Time - minutes High Fidelity Dynamic Operations

The Concept of Data-to-Applications

Performance Management Data & Modeling Workflow

Process sensor data Data and Computation Management Dashboard

Ref Arch Ref Arch Local/Global Data Collection Data Collection Manufacturer Manufacturer Data Integrated Productivity Manufacturer Supplier Real-time Warehouse Metric Dash Board

Encrypted links

Data Real-time Action & Risk Validation SM Platform App Support Workflow, App Data and Computation Services Reduced EPM Order Model App from Scenarios Toolkit App

Risk Scenarios Linked Apps to Form Function App Major Platform Concepts

• Multi-Layer Workflows interface with control and automation and factory optimized workflows • Real-time is defined by the workflow & actionable objective • Data-to-Application instead of Application-to- Data • Workflow as a Service (Wfaas)

Implementation

ENGINEERING THE PLATFORM FOR THE USE CASES Local Web Server Praxair SMR Process Example Data Data Control Automation Proprietary Workflow

Process Data New ROM Transfer Transfer Workflow Control Server Local Workflow Storage Data Validation Service and filtering Framework

Validated Data ROM Accepted

Update ROM Offline CFD ROM CFD Runs using CFD Simulation Preprocessing Output with ROM Validation

Rerun ROM

Batch Scheduler

Computational Resources SMLC Concept Workflow as a Service (WfaaS)

Factory Data Control & Automation Workflow (WFaaS) Workflow Provisioning Orchestration

Tasking State Proprietary Workflow Security Provenance

Application Instances WfaaS Integrated with SaaS, PaaS, IaaS

Workflow (WfaaS) /UCLA Services Factory Data Control & Automation Provisioning Orchestration Workflow Technical Computing Marketplace Tasking State Buyer/User (SaaS)

Proprietary Security Provenance Buyer Buyer Portal Workflow Dashboard Catalog Apps

Seller/Provider (PaaS)

Seller Software Dev Tools Dashboard Images

Application Instances Compute Platform (IaaS)

Software / Cycles Storage Licenses Nimbis Secure Cloud Portal Architecture Data and Application Management Foundation Web Browser / Desktop Application

Nimbis URL Dispatcher Caching Template Ecommerce Subsystem View (NES) Model Browse, Configure, Price, Purchase Message Queue Database HTTPS / SSH VPN / VNC

Nimbis Broker Asynchronous Task Queue Subsystem (NBS) Tasks Job/Session Management Resource/License Metering HTTP / REST / SOAP OAuth-OpenID

Compute Remote Platform Compute Provider Interface (CPI) Access Node License Manager PBS Application Images Shared Storage

Nimbis Services Inc. Proprietary Open Architecture Workflow Construction & Management SM Platform Apps Store, Shared Market Place & Distribution Hub Multiple Service Environments

“Apps” Store

Check Table Dashboard Process & Line Set Calculate Optimal Machine Recommend Integrated Point Conditions Machine, Energy, Usage Product Metric Tradeoff Points Metric Library of Update ROM Offline CFD Workflows CFD Runs using CFD Simulation ROM Preprocessing Output with ROM Sync

Machine, Workflow CFD CFD Runs Energy, App Toolkits Preprocessing Components Product Metric

Machine Data ROM Apps as a Service energy Definition Template CFD usage Maps for SMR calculation Apps as code module Breakthrough Systems Deployment

Data-to-Apps Paradigm for Broad Access

• Inverts current Apps to Data approach • Facilitates big data apps • Distributes App support • Separates proprietary and shared • Layers security Composable Sensor Based SM Systems

• Apps store • Data, metrics, models, actions, displays • Increased 3rd party contribution • Real-time systems across large time scales Workflow Based Architecture

• Composability & customization • Design to manufacturing models • Workflow libraries • Technology insertion

SMLC Commitment to a Comprehensive Approach

ENTERPRISE OPTIMIZATION & Enterprise SUSTAINABLE PRODUCTION Business System • Higher value products • Improved quality • Zero downtime Suppliers • Increased equipment life / utilization ENERGY, AGILE DEMAND-DRIVEN SUSTAINABILITY, EH&S SUPPLY CHAINS • Improved safety • Higher product availability • Reduced energy • No inventory and emissions • Product lifecycle Factory • Highly sustainable management

Distribution Smart Grid Center

Customer OEM Machine Builders

SM: An Enabling Technology

• National Network for Manufacturing Innovation (NNMI) • http://manufacturing.gov/docs/NNMI_prelim_de sign.pdf Possible focus areas: “Enabling Technology: Creating a smart-manufacturing infrastructure and approaches that integrate low-cost sensors into manufacturing processes, enabling operators to make real-time use of “big data” flows from fully instrumented plants in order to improve productivity, optimize supply chains, reduce costs, and reduce energy, water, and materials consumption.”

The infusion of intelligence that transforms the way industries conceptualize, design and operate the manufacturing enterprise. https://smartmanufacturingcoalition.org http://smartmanufacturing.com