https://smartmanufacturingcoalition.org http://smartmanufacturing.com

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

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

Machining Operation

General Dynamics Scranton, PA

http://afc-holcroft.com/products/continuous/roller-hearth

Holcroft Continous Roller Hearth

http://afc-holcroft.com/userfiles/file/pdf/ConveyorFurnace_Brochure.pdf

General Dynamics Scranton

Hot Forging Heat Treatment

General Dynamics Scranton, PA

General Mills Networked-Based Manufacturing

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 Green Light

Analyze - to put into production Make – right ingredients – confirmation on recipe Release – meet requirements to release

Mapping SAP information Into operation

Graphics courtesy of Rockwell Automation

Check status

SMR High Fidelity Model Validation

Web portal Specify parameters; submit

workflow

Display results; validate New parameters; validate Update operations

Evaluate new operating modes

Collect data; validate model New temperature conditions Estimate time

Octave

Reduced Order Model

Sensors

Smart Manufacturing’s Commitment to a Comprehensive Approach

Manufacturing Methods from Macro View

An Industry-Driven Open Architecture

Shared Infrastructure

SMLC Partnerships “Information that drives the next century’s structural shift in manufacturing.”

Smart 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

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)

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

Enhanced management complex behaviors

Performance management global integrated decisions

Variability reduction

Design models in production

Benchmarking machine-product interactions

Rapid qualification components products materials

Untapped enterprise degrees of freedom in efficiency, performance, and time

In situ measurement and integrated value chains

Product/material in-production ability

Machine-power manage management

Integrated computational materials engineering (ICME)

Enterprise analytics and business operational tradeoff decisions

Tracking, traceability and genealogy

New product, material technology insertion

Adaptable machine configurations

Configurable data and analyses for rapid analytics and model development

External partner integration and interoperabilty

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

• 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

A Set of Issues Beyond Individual Company

Technical and Business Drivers for Shared Infrastructure

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

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

Dept/SMM Small & Medium

Enterprises Manufacturing

Consortia

Modeling & Interoperability

Protocols IT Providers

Key Development

Resources Universities, SMM’s

Integrators, Labs

SMLC Industry-Driven Integrated

Performance Metrics

Micro, Meso, Macro

SMLC Industry-Academic-Government Platform Collaboration Model

Marketplace

Real-time Data & Modeling Workflow & Metric Toolkit/ App Development

SM Platform Open-architecture

Cloud-based

Test Bed Manufacturer

& Supplier Crosslinking

Engagements UCLA

Apps & Toolkits

CommunityResources

& Data Services

Machine Product Management

In Production High Fidelity Modeling Design and Planning Dynamic Decisions

Enterprise & Supply Chain Decisions

Benchmarking Rapid Qualification

Variability Management Real-time Plan Passes

Performance Management Tracking, Traceability

ICME

Composable Workflows

Apps & Toolkits

Advanced Sensing, Control & Automation, Platform Modeling & Dynamic Orchestration of Manufacturing Intelligence in

Heterogeneous Manufacturing Enterprises defined by SEAMs ASCPM

• Location where two or more parts of a manufacturing enterprise or supply chain are joined together

• Parts differ by time horizon, lexicon, technology, human in loop, culture, business drivers, vendors, or priorities.

System 1 System 2

Seam

SM Platform enabled virtual connection

Interfaces

Smart Manufacturing: Multi-Layered Seams, Time, Data & Action

Machines – People - Materials Dynamic Manufacturing Ecosystem

Design Data

Product Manufacturing

Materials & Process Tech Prototype Qualification In

Service

Macro Layer

Meso Layer

Micro Layer 1000s control loops Time - minutes

100s control loops Time -hours

10s control loops Time – days

Focus: 10x Multiple Pass Variability

Reduction; Supply Chain Information

Busi

ness

Sys

tem

s

Cont

rol &

Aut

omat

ion

Focus: 100x Event Variability/Tradeoff

Adjustment; Dynamic Performance Mgmt.;

Integrated Metrics

Focus: Insertion, Qualification, ICME, High

Fidelity Dynamic Operations

Smart Manufacturing based on ISA 95

Smart Manufacturing & Vendor Products

SM

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

Smart Manufacturing Open Architecture Platform

Composabilty

Control & Automation Propriety Optimized

Automation Workflows

Data Partnership Workflow

Orchestration

Sensor Data

Market Place Data collection,

modeling & Synchronization multi-scale time requirements embedded

Data collection, modeling & synchronization defined by workflow

No single scale time requirement in workflow

Decision

Design to manufacturing Workflow libraries

Separate Data & apps

Data to apps paradigm

Workflow (WfaaS)

Data-based Workflow Orchestration

Proprietary Workflow

Provisioning

State Tasking

Orchestration

Security Provenance

Application Instances

Selectable Apps

SM Platform Architecture

Provisioning

Sensor Network

Proprietary Platform

SM Platform Secure Data Interface and Workflow Architecture

OEM 1 Analysis BPM/Kepler Workflows

Sensor Network

Proprietary Platform

OEM 1

DOE Tesbed Marketplace

SM Apps & Applications

Dash Boards

UCLA/Nimbis Admin

User & Role Authentication

Browser and Remote Desktop Access

Supplier 2

Platform Historian 2

Visualization Workflows

Metric APP Model Visualize Commercial viewer(s)

Platform Historian 1

DOE SM Cloud Platform

Visualize APP

Open Data Model

DMZ service

DMZ server

Https:

FTP to PI

SM DMZ

SM Connect Supplier 2 BPM/ Kepler Workflows

Secure I, P and SaaS

Secure Data Highways

Data & Device Integration & Orchestration

Smart Factory Manufacturing

Smart Enterprise Manufacturing

Manufacturing Health & Sustainability

Collective Innovation &

Practice

Converting Data to Information

Converting Information to Knowledge

Converting Knowledge to Wisdom

Open Architecture

Data Valuation Collective vs. Proprietary

Practice Valuation Collective vs. Proprietary

The Business Model of Data

IoT

Big Data

Smart

Collective Wisdom

The Business of Open Architecture Market, Valuation of Data & Innovation

Performance Metrics with Platform

Year 1 Year 2 Year 3 Year 4 Year 5 notes

Decrease R & D cost/risk

25% 30% 35% 40% 50% Compared to no platform baseline; 1st year decrease - data & modeling infrastructure; 2nd year progressive decrease - building on shared research

Accelerated pace of R & D outcomes

2 years to 1 year

+5% faster +10% faster +15% faster

+20% faster 1st year reduced duration - flexibility with modeling infrastructure; 2nd year progressive - more interface apps, better use standards, better modeling tools, consolidated experience

Decrease in replication/deployment cost/risk & accelerated pace

60% 1 – 2 replications

65% multiple replications

70% multiple replications

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

Retrofit modeling - waste heat minimization/energy productivity - base no advanced technology (See DOE proposal)

20% 30% 35% 40% 50% Advance control and low hanging fruit practices 20 – 25%; advanced real time modeling & integration next 20%; sophisticated integrated modeling next Calculated for control and IT retrofits for existing process – measurements, new, dynamic operating conditions; does not account for potential for new equipment

1 year shift

Low hanging

fruit

1st phase energy R & D

2nd phase energy R & D

Platform Energy Economics 25

What is Smart Manufacturing

Internal & External Value Chain Networked-Based Manufacturing

Supply Chain Distribution Center

Customer

Business Systems, ERP

Smart Grid

Smart Factory

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

EDI transaction lot & quality certifications

Tracking & traceability

More customer freedom To customize

Graphics courtesy of Rockwell Automation

Minimum just in case inventory & corrective actions thru entire system

Chain of custody

Order adjustment Reduce premium shipments

Use Cases Mike Yost Mesa

AMP 2.0 Recommendations