Manufacturing Systems: From Sustainable to Smart

Dr. Sudarsan Rachuri Program Manager

Systems Integration Division Engineering Laboratory

NIST sudarsan@nist.gov

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Outline • Introduction • Part 1- Smart Manufacturing System

– Program objective and focus

– Projects

• Part 2 - Sustainable Manufacturing - Performance • Summary

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Smart Manufacturing Systems Design and Analysis

Objective To deliver measurement science, standards, and tools needed to design and analyze SMS based on a cyber-physical infrastructure for digital and manufacturing systems by 2018.

Projects: • Reference Architecture for Smart

Manufacturing Systems (RASMS) – define the make-up of the smart

manufacturing system

• Modeling methodology for Smart Manufacturing Systems (MMSMS)

– a systematic way of modeling and integrating the SMS components

• Real-Time Data Analytics for Smart Manufacturing Systems (DASMS)

– workflow standards for manufacturing data analytics including causal analysis and performance predictions under uncertainty

• Performance Assurance for Smart Manufacturing Systems (PASMS)

– Methods for assuring performance of Smart Manufacturing Systems

Standards and Measurement Science

for Smart Manufacturing Systems

Design and Analysis

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Smart Manufacturing Systems Design and Analysis

Reference Architecture for Smart Manufacturing Systems

Modeling methodology for Smart Manufacturing Systems

Real-Time Data Analytics for Smart Manufacturing Systems

Performance Assurance for Smart Manufacturing Systems

Performance of SMS

Models and standards SysML, BPMN, Modelica

Standards Reference Architecture OAGi standards ISA 95

Performance metrics and Standards ASTM E60.13

Performance metrics and Standards STEP-NC, MTConnect, PMML

We need build a smart Model of Manufacturing System

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Physical Artifacts

Information Artifacts

Resources

Physical Artifacts

Information Artifacts

Resources

Raw materials

Components

Auxiliary materials

Energy

Water Emissions

M1

Mi Mn

Mi – Machine i Pi – Process i Σ

Products Co-products By-products Waste

Predict

Control

Plan - Predict – Do – Study - Act

Based on CPS Architecture build a Reference Architecture

ISA-95, Image courtesy: Automation world

Improving Manufacturing Efficiency through Predective Analytics

• 5% decrease in batch cycle time • 10% improvement in machine reliability • 10% reduction in water consumption • 5% reduction in energy costs

Source: www.ge-ip.com

We need to achieve data compression and timeliness across Layers

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Petabytes Exabytes

Gigabytes Terabytes

Kilobytes/second Processing

Data Compression

Filters

Filters

Inte

llige

nt

dat

a re

du

ctio

n

*– Extraction, cleaning, annotation

Protocols/standards

Protocols/standards

Protocols/standards

Data Structured, multi-structured, Streaming, DAQ, Data pre-processing*,

Descriptive analytics

Analytics Predictive Models, Algorithms, Analytics engine, Model composition,

Uncertainty quantification

Integration Rules Engine, Distributed and real-time computing, Apps, APIs, Web

Services

Decision Business and User Goals

Manufacturing Business Intelligence (web, desktop, mobile apps),

Dynamic production system, Operations

Megabytes

Clo

sed

loo

p s

yste

m

Years -> Months -> Weeks Days

Seconds or less

Real time/ On time

Tim

elin

ess Hours Minutes

Manufacturing Execution System, Manufacturing Operations Management

SCADA, PLC, HMI, DCS

SCADA Supervisory Control and Data Acquisition PLC Programmable Logic Controller HMI Human Machine Interface

We need to understand the Predictive Analytics Workflow

Data extraction/Data

stream

Input validation

Decision Storage/Decision Processing

Data Post-processing

Predictive Model

Data Pre-processing

Outliers, missing values, invalid values

Normalize, Discretize, Filter etc.

Scaling, Decision,

Scores etc.

Raw input

s Prediction

Standards and protocols for this information flow

• Standardize the predictive models • Model definition • Model Composition • Model chaining

Sender

Receiver

Receiver

Sender

Standard

Protocol Standard

Interface Standard

define both the transmitter and receiver function at the same time. ensures

compatibility

Data visualization

Promise of Big Data Analytics Solution!

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* SM: Smart Manufacturing * HDFS: Hadoop Distributed File System * SME: Small & Medium Enterprise * CAPP: Computer Aided Process Planning * FDC: Fault Detection & Classification System * YMS: Yield Management System * SVM: Support Vector Machin

Shop Floor Layer

Data Layer

Analytics Modeling Layer

Integration Layer

Application Layer

Static Data Dynamic Data

Statistics Approach Machine Learning Approach

Model Life Cycle Life Cycle Control

Feed

back

Con

trol

Manufacturing Process

Big Data Infrastructure Layer

CAPP, MES, FDC, YMS, …

R, … Neural Network, SVM, Decision Tree, …

R Hive, Hadoop, HDFS, MapReduce, …

Process Plan (STEP-NC), Production Plan, Master, …

Monitoring (MTConnect), Metrology, Defect, …

Creation Deployment In-Use Disposal Duration Control, Uncertainty Resolution

Part 2

• Sustainable Manufacturing - Performance

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Quick motivation of the sustainable manufacturing

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1. What are the fundamental measurement science and standards to enable sustainable manufacturing? energy, material, and performance metrics for manufacturing

process characterization with associated uncertainties 2. How to enable standardized sustainability assessment methods

analytical computations and optimization for characterizations and synthesis

3. How to enable manufacturing systems integration for sustainability? information models, model-based systems engineering, simulation

Sustainable Processes and Resources

Integration Infrastructure for Sustainable Manufacturing

Standardized Assessment Methods

Measurement Science

Manufacturing Systems

Integration

Cost

Quality

Productivity

Manufacturing Performance Dimensions for sustainability – A systems approach

Sustainability (a systems approach to optimize on all

dimensions)

Our focus – Resource efficiency For manufacturing

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Manufacturers are Challenged by Increasing Sustainability Requirements

Manufacturers need to cope with existing and new standards (voluntary and mandatory) that:

1. Continue to expand across product categories and life cycles

2. Impact innovation and competitiveness

3. Introduce complex product data

• Collect

• Secure

• Verify

• Validate

4. Can create conformance issues with suppliers

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We need a Framework for Metrics and Measurements for Sustainability Performance

What to measure How to measure How to document How to verify/validate

Indicators /metrics Metrology

Data availability

/Generation

LCA tools

Standards based

Compliant based

Measure performance

International

National Product level

Process level

Service level

Life cycle (cradle to cradle

and cradle to grave)

Accuracy Precision

Units Uncertainty

Reference data Reference materials

Measurement methods Predictive tools

Information models Standards

Measurement methods Measurement devices

Business tools

Engineering tools

GRI CPD

Dow Jones ..

Voluntary GHG protocol

ISO 14000 ISO 19011 ASTM E60 IPC 1752

Regulatory RoHS

REACH ELV

WEEE USEPA

Private/Public partnership

EU ECHA EMAS ISO

..

Federal State

Regional

How to model the Information Flow? 15

Generic Models are needed for understanding sustainability impacts of products and processes

• We need a modeling platform that includes a generic model of product definition and methodologies for Life Cycle Analysis and Synthesis as the foundation for design for sustainability (DFS) framework, to do trade-off analysis of various design choices.

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Product/ Assembly

Form Function Behavior

Structure

e-BOM m-BOM

Geometry

BOS

BOC

Material

Realization

Process

Unit Process

Product Use Inputs Energy Material

..

Outputs Useful

Harmful …

Functional Unit

Process focus

EPD

BOP

LCA tool Or

DFS

BOM – bill of materials BOS – bill of substances BOC – bill of carbons BOP – bill of processes EPD – environment product declaration LCA – life cycle assessment

Description of the research work

1. Classification – an important aspect of measurement science – Sustainable manufacturing terminology and metrics

– Material information model for energy and material efficiency

– Classifying manufacturing process

2. Methodology for composing manufacturing processes and sustainability optimization

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1. Classification – an important aspect of measurement science

a) Formal methodology for sustainable manufacturing terminology and metrics (ontology)

b) Material information model for energy and material efficiency

c) Formal methodology for classifying manufacturing process (ontology)

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1 a) Formal methodology for sustainable manufacturing terminology (ontology)

• Develop the taxonomy as an extensible schema, to classify a wide range of terms

• Construct terminology as an ontology, capturing relationships to other terms and concepts

• Present the information using an interactive visual interface, using various shapes and colors to easily identify and understand concepts

• Automatically generate formal representations of data, for integration with other engineering tools

Search:

Product Category Definition: Group of products that can fulfill equivalent functions.

Source: link

Intelligent

querying

Detailed

description of

selected term,

with links

Links to

related

documents

Interactive

visualization of

networked

information

19 http://sourceforge.net/projects/novis/?source=directory

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1 a) Sustainable Manufacturing Metrics Repository • Contain multi-dimensional indicators and metrics • Provide in-process and off-line sustainability measures to SME*

<Five categories>

<e.g., Indicator list of environmental stewardship> * SME: Small and Medium-sized Enterprise [Joung, C., et al, “Categorization of indicators for sustainable manufacturing,” Ecological Indicators, 2012]

http://www.mel.nist.gov/msid/SMIR/Background.html

1 b) Material information in lifecycle

Alloy7475-T61 sheet design

model

Lots of Alloy7475-T61 sheet In manufacturing

Alloy7475-T61 in a product

Alloy7475-T61 chips and waste

Alloy7475-T61 in recycle

Alloy7475-T61 sheet in material catalog

AL7475-T61 test sample

Material development

and test

Engineering analysis in

product design

Manufacturing planning

Manufacturing execution and

monitoring

Reporting and Recycling

Physical and mechanical property Appearance parameters

Part design model

Bills of Substances

Production technology

Test organization

Test methods and tools

Measurements

Test data

Material processing data

Chemical structure

Physical and mechanical property

Chemical structure Cost and availability

Purchase history Transportation data Quality test data Production technology

Bills of Substances

Material declaration

Chips and waste amount

Cost

Recycle efficiency

Recycling methods Recycling efficiency

Material object

Legend

material information

Lifecycle of material information

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1 b) Materials Information Challenges

Material Design

Product Manufact

uring (CAPP/MES)

Material Selection

(CAx/PDM)

Material Resource Planning

(ERP)

Material Information

Model

• Process characteristics for materials • Material manufacturability • Supply chain visibility • Material quality

• Cost • Bills of Materials • MSDS • Restricted materials (EU RoHS/REACH) • Material lifecycle (Reusability, Recyclability, …)

• Material constitutive model

• Experiments & Test data

• Material Properties

• Sustainable materials

• Engineering performance • Product functionality • Product quality (durability, reliability, …) • Sustainability

• Industrial database • Material info. exchange (MatML, MatDB, ..) • Material Declaration (RoHS/REACH, IPC 157x, …) • High level MIM

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1 c) We also need a good Manufacturing Process Classifications

• Clustering of similar processes

• Easier grouping for purposes of analysis

• Sustainability characterization through understanding complex relationships

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Faceted Classification of Manufacturing Processes, Senthilkumaran Kumaraguru, Sudarsan Rachuri and David Lechevalier, Accepted for publication - The International Journal of Advanced Manufacturing Technology

A quick look at Types of Taxonomies

• Lists (controlled vocabularies) – Picking from a predefined list of processes

• Synonym lists – Can be used to track words that represent same things

• Hierarchical – Parent/child, broad/narrow, is a part of, is a type of

• Faceted – Hierarchies with a labeled category called facets

• Ontologies – Faceted taxonomy with all ambiguities removed and all

concepts completely described

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Faceted Classification of Manufacturing Process Facet – an attribute of a group of categories

Interaction – Relationship of the process with its category Facets

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Visualizing network of processes

Brake forming (sheet metal bending) process showing relationships with its classifiers

Graph Visualization results for the query

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Process clustering based on Electricity requirements and water requirements

27 Gutowski, T., J. Dahmus, and A. Thiriez. “Electrical Energy Requirements for Manufacturing Processes," 13th CIRP International Conference on Life Cycle Engineering, Leuven, Belgium, May 31-June 2, 2006.

Electricity requirements Water requirements

Comparing processes

1,E+05

1,E+06

1,E+07

1,E+08

1,E+09

1,E+10

1,E+11

1,E+12

1,E+13

1,E+14

1,E-06 1,E-04 1,E-02 1,E+00 1,E+02

Ele

ctri

city

re

qu

ire

me

nts

(J/

kg)

Process rate (kg/hr)

Polymer Metal Metalloid

1,E+05

1,E+06

1,E+07

1,E+08

1,E+09

1,E+10

1,E+11

1,E+12

1,E+13

1,E+14

1,E-06 1,E-04 1,E-02 1,E+00 1,E+02

Ele

ctri

city

Re

qu

ire

me

nt

(J/k

g)

Process rate (kg/hr)

Chemical Electro Mechanical Electro optical Mechanical Thermal

Material type facet view Energy type facet view

Here we can infer that even though injection molding and rapid thermal processing are thermal in nature, the type of material influences the energy requirements. As semiconductor processing needs more energy to process silicon typically a metalloid rather than polymer processing as in case of injection molding

Description of the research work

1. Classification – an important aspect of measurement science – Sustainable manufacturing terminology and metrics

– Material information model for energy and material efficiency

– Classifying manufacturing process

2. Methodology for composing manufacturing processes and sustainability optimization

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Methodology for composing manufacturing processes and sustainability optimization

M a

M b

M c

A a

A b

Cost CO2

Product 2

Part1

Part2

Product 1

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A manufacturing problem in SPAF

string Id = “twoProductsManuf”; include context productionSequence(); {string} Id.inputFlows = {“part1in”, “part2in”}; {string} Id.outputFlows = {“product1”, “product2”}; string part1in.matchName = "part1"; string part2in.matchName = "part2";

SPAF model

include productionDemand(); include twoProductsManuf (); twoProductsManuf.totalCO2 ≤ 50; minimize twoProductsManuf.totalCost;

A standard Optimization Model such as OPL/AMPL/AIMMS

MP solver

CP solver …

e.g., IBM CPLEX

Formulate a SPAF optimization query

SPAF – Sustainable Process Analytics Formalism OPL - Optimization Programming Language

set prd; # products set raw; # raw materials param T > 0 integer; # number of production periods param max_prd > 0; # maximum units of production per period maximize total_profit: sum {t in 1..T} ( sum {j in prd} profit[j,t] * Make[j,t] - sum {i in raw} cost[i] * Store[i,t] ) + sum {i in raw} value[i] * Store[i,T+1];

Create a SPAF process model

SPAF model

Compile it into a standard MP model Optimization solver

Optimization results

AMPL - A Mathematical Programming Language AIMMS- Advanced Interactive Multidimensional Modeling System

string Id = “twoProductsManuf”; include context productionSequence(); {string} Id.inputFlows = {“part1in”, “part2in”}; {string} Id.outputFlows = {“product1”, “product2”}; string part1in.matchName = "part1"; string part2in.matchName = "part2";

Update SPAF model

Standards? We’ll see More of it in the Future…

31 Sources: Industrial Environmental Performance Metrics, National Research Council, 1999; Forecasts: Internal analysis.

Pre-1970 1970s 1980s 1990s 2000s 2010 and beyond

• Noncompliance • Waste • Pollution

• Pollution Control • Compliance

• Pollution Prevention • Environmental

Management systems

• Product Stewardship • Design for environment • Life-Cycle assessment

• Eco-efficiency • Environmental cost

accounting systems

Unprepared

Reactive

Anticipatory

High Integration

Constraints on Material Usage

•Sustainability Product Design

•Stricter Pollution Prevention •Low/Zero Carbon Technology

•Life-Cycle Reporting

Inability to Externalize

TRANSPARENCY

Environmental Management Learning Curve

A clear and well defined standards strategy is essential to achieve results and impacts

• Established ASTM E60.13 (Vice-chair: Sudarsan Rachuri) – WK35702 New Guide for Evaluation of Environmental Aspects of Sustainability of Manufacturing

Processes (Technical Lead: Paul Witherell)

– WK35703 New Terminology for Standard Terminology for Sustainable Manufacturing (Contributors)

– WK35705 New Guide for Sustainability Characterization of Manufacturing Processes (Technical Lead: Kevin Lyons)

– WK38312 New Classification for Waste Generated at Manufacturing Facilities and Associated Claims. (Contributors)

– Aggressively recruiting manufacturing industry leaders, SMEs, and software solution provider.

– Liaison with ISO TC 207: ISO 14000 standards

– Evaluated new opportunities

• ISO TC 242 - Energy Management

• ISO TC 257 - General technical rules for determination of energy savings in renovation projects, industrial enterprises and regions

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Thank You

• Smart Manufacturing Design and Analysis

http://www.nist.gov/el/msid/syseng/smsda.cfm

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