smart manufacturing as a real -time networked...
TRANSCRIPT
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)
3
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
4
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
Implementing 21st Century SM Report (2011)
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
Energy Supply Production and Delivery Customers
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
• Hosted computing improves results at a lower cost
• Common infrastructure facilitates supply chain collaboration
Design Operations
• Low cost sensors and wireless enable real time decisions
Machine Operations & Line Management Trade-Offs
Machine Function Benchmarking & Integrated Line and Energy Management Managing Power from the Grid
General Dynamics
FORD In-Production Virtual Aluminum Castings
Aging temperature 240C for 5hrs
210 230
205
Aging at 250C for 3hrs
Optimized Heat Treatment Process Faster and Stronger !!
220
Initial Heat Treatment Process
Target Strength = 220 MPa
John Allison AIChE 2010
General Mills Farming
Distributor
Supply Chain
Customer
• Customers “pushing” demands • Tracking & Traceability
Manufacturing Plant
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Supply Chain Distribution Center
Customer
Business Systems, ERP
Smart Grid
Smart Factory
Recipe Management Mapping formula into operating recipes
EDI transaction & quality certifications
FDA Tracking & traceability
General Mills Networked-Based Manufacturing
Intelligence & Collaborative Manufacturing
Green Light Analyze - to put into production Make – right ingredients – confirmation on recipe Release – meet requirements to release
Mapping SAP information Into operation
Master Data (BOM,Specs,Vendor,Ingredients,FP)
Dire
ct
Cons
umpt
ion
Core Systems
Data Input
Core Functions
Raw
Mat
’l In
vent
ory
Fini
shed
Pro
duct
In
vent
ory
Prod
uctio
n
Hist
ory
Plan
t Flo
or
Inve
ntor
y
Dem
and
Plan
Prod
uctio
n O
rder
Line
Sche
dule
MQIS MES SAP ERP Red Prairie SAP APO SAP PLM SAP MRP
Value Creation Green Light to Convert
Green Light to Ship
Demand Driven Supply Chain
Wor
kFlo
w
Lot T
rack
ing
Overusage
Opt
imiza
tion
Engi
ne
Trace/Recall BOM Validation Yard Mgmt
Optimized Inventory
Business Applications Directed Work
Supplier Managed Inv Line Supply Bin Mgmt
Allergen/Micro WorkFlow eCOA
GM’s ECO System of “ STUFF”
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
META 4 Interoperable Supply Chain
Network Control, Automation,
Optimization Management & Decision
Meta 2 Demand-Dynamic
Customer to Source Variability Planning
Multi-Dimensional Smart Manufacturing
Meta 3 Higher Fidelity Production
Real-time Qualification Integrated Computational
Materials Engineering Materials & Energy Mgmt.
Meta 1 Integrated Workforce,
Cyber, Physical System Performance
Variability Reduction Benchmarking
Challenge 2 Integration of manufacturing enterprise data, control, automation, management and optimization infrastructures
Challenge 4 Precompetitive and competitive community source modeling innovation & simulation assimilation platform
Challenge 1 Factory and supply chain demonstrations sites of applied manufacturing intelligence
Challenge 3 Real-time syncing virtual models and physical operations
The Technical Basis for Collaborative Manufacturing and the SM Platform
Enabling New & Dormant Technologies
11/1/11
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SMEs Small & Medium
Enterprises Manufacturing
Consortia
Standards and Reference
Architecture IT Providers
Key Development
Resources Universities, SME’s
Manufacturers, Labs
SMLC Industry-Driven Integrated
Performance Metrics
Micro, Meso, Macro
First Concept of the Smart Manufacturing Platform Infrastructure for Real-Time Data Driven
Modeling and Simulation
Community Source Market Place
Real-time Data & Modeling Workflow To& & Metric Toolkit/ App Development
Real Time Virtual Manufacturing Demonstration Facility (VMDF)
Pre-competitive & Competitive
Hub
Test Bed Manufacturer
& Supplier Crosslinking
Engagements UCLA
Apps Store Cloud
Services
Variability Management
Real-time Plan Passes
Community
Source Resources
Benchmarking
Rapid Qualification
ICME
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 Data
MDSM Program “Host” Manufacturing
Initiatives
Virtual MDSM
Host • Dash Board •Collaboration
Product Manufacturing
Materials & Process Tech Prototype Qualification In
Service
Macro Layer • Product Volume • Scheduling • Supply Chain
Meso Layer • Management • Machine Flow • Optimization
Micro Layer
APP Store • Reference Flows • Process Models
• Control •Metrics
• Sensors/Actuators • Control/Optimization • Automation
People Involved Integrated Metrics & Decision Making
Conditional decisions Model building &updates Model insertion
Workflow Distinguished from Control & Automation
Check Table Optimal Machine
Usage
Calculate Machine, Energy,
Product Metric
Dashboard Recommend
Tradeoff Points
Process & Line Set Point
Conditions
Run Machine Usage Pattern-Based Analyzer
Update Machine Usage Model
Build Table Optimal Machine Usage Windows
New Machine Maintenance Process Data
Process & Line Data
Factory Data Control Automation Factory Workflow
General Dynamics
Benchmarking Model
Table Model Accepted
Workflow Service
Framework
Computational Resources Batch Scheduler
Machine Benchmark
Data
Multi-Layered Smart Manufacturing Management (MLSMM) Time Managed as Workflow Not Control
Transformational Machines – People - Materials Dynamic Manufacturing Ecosystem
Design Data
Product Manufacturing
Materials & Process Tech Prototype Qualification
In Service
Macro Layer
Meso Layer
Micro Layer 1000s of control loops Control points -
Manpower – 100X Time - minutes
100s of control loops Control Points - ? Manpower – 10X
Time -hours
10s of control loops Control Points - ?
Manpower - X Time – days
Current Practice – One Pass per Day per
Event; Too Late, Stale Data, Slow Responsive
Manufacturing
Goals: 100x Event Variability Adjustment Capability & Dynamic
Certification Improvement
Focus: Integrated metrics, Qualification,
Computational Materials Engineering, High Fidelity Dynamic
Operations
The Concept of Data-to-Applications
Ref Arch
Data Collection Manufacturer
Manufacturer Real-time
Manufacturer Data Warehouse
Performance Management Data & Modeling Workflow
Data Validation
App
Local/Global Integrated Productivity
Metric Dash Board
Process sensor data
Ref Arch Data Collection
Supplier
Data and Computation Management Dashboard
EPM App from
Toolkit
Risk Scenarios App
Reduced Order Model
Scenarios App
Real-time Action & Risk
Support App
SM Platform Workflow, Data and
Computation Services
Encrypted links
Linked Apps to Form Function
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)
ENGINEERING THE PLATFORM FOR THE USE CASES
Implementation
Process Data Transfer
Process Data
Data Control Automation Proprietary Workflow
Praxair SMR Example
ROM Validation
Local Storage
ROM Accepted
Rerun ROM
Workflow Control Server
Data Validation and filtering
Local Web Server
Workflow Service
Framework
Computational Resources
Validated Data
Batch Scheduler
New ROM Transfer
CFD Runs Update ROM
using CFD Output
Offline Simulation with ROM
CFD Preprocessing
Workflow (WFaaS)
SMLC Concept Workflow as a Service (WfaaS)
Factory Data Control & Automation Workflow
Proprietary Workflow
Provisioning
State Tasking
Orchestration
Security Provenance
Application Instances
Workflow (WfaaS)
WfaaS Integrated with SaaS, PaaS, IaaS
Compute Platform (IaaS)
Cycles Software / Licenses Storage
Technical Computing Marketplace
Seller/Provider (PaaS)
Seller Dashboard Dev Tools Software
Images
Buyer/User (SaaS)
Buyer Dashboard
Buyer Catalog
Portal Apps
Factory Data Control & Automation Workflow
Proprietary Workflow
Provisioning
State Tasking
Orchestration
Security Provenance
Application Instances
/UCLA Services
Web Browser / Desktop Application
Caching URL Dispatcher
View
Model
Template
Tasks
Asynchronous Task Queue
Message Queue Database
Compute Provider Interface (CPI)
HTTP / REST / SOAP
Nimbis Ecommerce
Subsystem (NES)
Nimbis Broker
Subsystem (NBS)
Compute Platform
Shared Storage
Browse, Configure, Price, Purchase
OAuth-OpenID
PBS
Job/Session Management Resource/License Metering
Remote Access Node
HTTPS / SSH VPN / VNC
License Manager
Application Images
Nimbis Secure Cloud Portal Architecture Data and Application Management Foundation
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 Optimal Machine
Usage
Calculate Machine, Energy, Product Metric
Dashboard Recommend
Tradeoff Points
Process & Line Set Point Conditions
CFD Runs Update ROM
using CFD Output
Offline Simulation with ROM
CFD Preprocessing
CFD ROM
Template for SMR
Apps as a Service Apps as code module
CFD Runs CFD Preprocessing
Machine, Energy, Product Metric
App Toolkits Workflow Components
Library of Workflows
Machine energy usage
calculation
ROM Sync
Integrated Metric
Data Definition
Maps
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
Smart Grid
Customer
Enterprise Business
System
Suppliers
OEM Machine Builders
Distribution Center
Factory
SMLC Commitment to a Comprehensive Approach
• Higher value products • Improved quality • Zero downtime • Increased equipment
life / utilization
• Improved safety • Reduced energy
and emissions • Highly sustainable
• Higher product availability • No inventory • Product lifecycle
management
ENTERPRISE OPTIMIZATION & SUSTAINABLE PRODUCTION
ENERGY, SUSTAINABILITY, EH&S AGILE DEMAND-DRIVEN
SUPPLY CHAINS
• National Network for Manufacturing Innovation (NNMI)
• http://manufacturing.gov/docs/NNMI_prelim_design.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.”
SM: An Enabling Technology
The infusion of intelligence that transforms the way industries conceptualize, design and operate the manufacturing enterprise.
https://smartmanufacturingcoalition.org http://smartmanufacturing.com