energy to ghg, water performance, sustainability …...smart manufacturing: encouraging paradigm...

Smart Manufacturing: Encouraging Paradigm Shifts In Process Operations-

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Energy to GHG, Water Performance, Sustainability

Indicators

Darlene Schuster Director Technical Entities, AIChE

November 2015

AIChE is on the frontier of chemical engineering research and development

to help address critical issues of today and tomorrow, as the incubator and

ongoing supporter of national high-tech knowledge centers.

Professional Development

& Technical Societies

www.aiche.org

Technical Entities (TEs): Providing Solutions for Society’s Grand Challenges

Center for Energy Initiatives

International Society for Water Solutions

Institute for Sustainability

Society for Biological Engineering

- International Society for Metabolic Engineering

Industrial Technology Alliances (ITAs): Providing Solutions for Industry’s Challenges

CCPS & DIERS address process safety

CHO II addresses pharmaceutical development & quality

CSTP & Cosmetics roundtable cover sustainability-- and metrics

DIPPR addresses quality of physical properties measurement

CCPS/DIERS CHO II CSTP DIPPR

National Network for Manufacturing Innovation (NNMI)

ON SMART MANUFACTURING

SMART IS here to stay…. DOE has announced a RFP for a

NNMI on SMART

Federal Plan to help revitalize American manufacturing and encourage companies to invest in the United States. (2012)

United States Grand Challenge: Companies, innovation, jobs, leaving the US

Current and potential NNMIs Name

Executive Director

Sponsors*

Year Formed Products & Services

America Makes Ralph Resnick 100 2012 3D printing, also known as additive manufacturing

Lightweight Innovations for Tomorrow

Lawrence Brown

6 2014 Lightweight technology development

Institute of Advanced Composites Manufacturing Innovation

Doug Parks – Chair

19 2015

Reduces technical risk and develops a robust supply chain for advanced composite materials in applications such as auto, wind turbines and compressed gas storage

Power America David

Danielson 3 2010

Develops advanced manufacturing processes that will enable large-scale production of wide band gap (WBG) semiconductors

Digital Manuf’g & Design Innovation Institute

Dean Bartles 12 2014 Encourages deployment of digital manufacturing and design technologies to become more efficient & cost-competitive

SMART ? ** SMLC –D. Swink * 20 2016** SMART Process Operations

Process Intensification?

?? ?? 2017? Process Design and Construction for industry

** In development and anticipated awarded in 2016

Sponsors include companies, non-profits, universities, governmental agencies

Defn of SMART

Smart Manufacturing (SM) is the application of real-time, networked and data based manufacturing Intelligence to facilitate dynamic market demand, added product value, and high velocity technologies and products with increased expectations for environmental sustainability and zero safety incidents.

Smart Grid

Customer

Enterprise Business

System

Suppliers

OEM Machine Builders

Distribution Center

Factory

• 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

8

ENTERPRISE OPTIMIZATION &

SUSTAINABLE PRODUCTION

ENERGY,

SUSTAINABILITY, EH&S AGILE DEMAND-DRIVEN

SUPPLY CHAINS

Courtesy of Rockwell Automation : Copyright © 2010 Rockwell Automation, Inc. All rights reserved.

The commitment to comprehensive design-manufacturing life cycle

T H E

V I S I O N

Open Architecture

Infrastructure &

Apps Store

Smart Manufacturing as a Real-Time Networked Information Enterprise

Open-architecture infrastructure for plug & play

Workflow Based architecture for composability and insertion

Composable sensor-based SM Systems

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

SMLC Partnerships

An Industry-Driven

Open Architecture

Shared Infrastructure

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 Mills,

General Motors, Praxair, Corning, Pfizer, NETL,

Alcoa, Center for Advanced Technology Systems/RPI

Design/Manufacturing Platform Providers –

JPL/NASA, UCLA, Rockwell, Honeywell, Emerson,

Invensys, Nimbis Modeling & Simulation Materials,

Design, Manufacturing – Caltech/JPL, NETL,

Argonne, UCLA, UT Austin, Tulane, NCSU, CMU,

Penn, Purdue Smart Manufacturing/Smart Grid –

EPRI Global Metrics/Outreach – AIChE, ASQ, AMT,

ACEEE, NCMS, MESA, MT Connect, Sustainable

Solutions, Spitzer & Boyes Agency partners – NIST,

NSF Regional Partners - Center for Smart

Manufacturing Innovation in CA (CMSI), Wisconsin

Manufacturing Institute Other - Association of State

Energy Research & Technology Transfer Institutions

(ASERTTI), National Association of State Energy

Officials (NASEO)

Design Operations Supply Chain

DOE Project Test Bed 1

Praxair dynamic energy management & cross unit performance

DOE Steam Methane Reformer (SMR) Project Overview

• Demonstrate Smart Manufacturing platform for energy saving applications

• Praxair Goals – Evaluate next generation technology for improved reformer temperature management

– Reduce energy costs and emissions while improving reliability

• Project started in September 2013. Port Arthur facility is the beta site – Partners: UT (modeling); Emerson (control); UCLA/Nimbis (IT platform); AIChE (metrics)

12 | Praxair Business Confidential | 12/15/2015

Technology for improved efficiency and reliability

-1.5

-1

-0.5

0

1400

1450

1500

1550

1600

0 5 10 15 20 25 30 35min

SMR Temperature (F)SMR Pressure (inWC)

Tube & Pig Tail TCs, and fixed IR imaging

Data driven and fundamental models Cloud based applications

ROT performance monitoring Manual burner valve adjustments

Measurement Modeling Monitoring and Control


Instrumentation Installation Completed at Port Arthur

North Side Wall

South Side Wall

4 cameras

Instrumentation ‒ 8 fixed infrared cameras ‒ 70 thermocouples ‒ 8 furnace fuel flow-meters ‒ Associated wireless/wired communication

~$1.1 MM

Sensing in ~80% of tubes

Row A Tubes

Tunnel A

Tunnel H

Row G Tubes

West Wall

4 cameras

Energy Intensity Reduction

Continuous Improvement

DOE Testbed #2

SMLC Project

Line Operations

DOE Project Test Bed 2 Energy Intensity Next Step improvement

General Dynamics Multi-Function Energy & Integrated Line Management

Heating and Forging Cutting and Machining

Power Mgmt and Energy Grid

16

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

Example Other Test Bed - General Mills

Green Light

Analyze - to put into production

Make – right ingredients – confirmation on recipe

Release – meet requirements to release

Mapping SAP information

Into operation

Workflow Construct 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

Bu

sin

ess

Sys

tem

s

Co

ntr

ol &

Au

tom

atio

n

Focus: 100x Event

Variability/Tradeoff

Adjustment; Dynamic

Performance Mgmt.;

Integrated Metrics

Focus: Insertion,

Qualification, ICME, High

Fidelity Dynamic

Operations

Review of Past and Existing Metrics

• Sustainability/sustainable development metrics/indices abound – EPA Framework for Sustainability Indicators: Database for Sustainability

Indicators and Indices

– NIST’s Sustainable Manufacturing Indicators Repository

• Start with AICHE Sustainability Metrics, monitor, finalize

Goals

KPIs

Metrics

Data

Material Intensity Mass of Materials Consumed - Mass of Products

Output

Basic Sustainability Metrics

Toxic Release Mass of Recognized Toxics

Output

Solid Waste

Output

Mass of Solid Wastes

Output:

Mass of

product

Functional

unit

Revenue

or

Value-

Added

Value-

Added

Energy Intensity Net Energy Consumed in Primary Fuel Equivalents

Output

GHG Emissions

Output

Pounds of CO2e

Pollutant Emissions Pounds of Pollutant Equivalents

Output

Water Consumption Volume of Fresh Water Consumed

Output

Developed by AIChE Industry roundtable cwrt (IfS) 2001

Enterprise Engagement with decision suport—KPI’s they need

• Responsibility for improving energy productivity and sustainability optimization belongs to all functions, e.g.

– Sales & Marketing – develop energy efficient portfolio of products – Finance – utilize accurate cost model for allocating energy use to products – R&D – develop energy efficient products both in manufacturing processes and customer

use – Process Engineering – identify annual energy cost savings in design stage of capital

projects – Production Engineering –assure yield and quality (and energy costs?) – Operations –reliability and asset optimization

Sales and Marketing Engineering Logisitcs Product Use Customer Use Disposal

Procurement Operations

Raw Materials DistributionManufacture Industrial Customer Use Disposal/ recycleEnd Use

Process Map for Business to Business

Process Map for Business

Focus Groups—who uses water data in making key decisions?

Responsibility for Water in Industrial complex?

How is data used in decision making?

Key data needed for Metric for KPI for decision maker.

NEXT STEPS?

Praxair Testbed

Auxiliary Utilities Used in process, not in

product

Reformer/Purification

Raw Materials

Recovered heat/ Steam

Water Input

Off-gas, Fuel

By-products used in other processes

On Site Waste Treatment

Purchased Off-site Energy

Energy Generated On-Site

Fuel

Product

Off Site

Emissions

Steam and/or electricity

Emissions

Fuel

Waste Haz and non-haz

Reformer Boundary

Water Discharge

Emissions

Facility Scale

Auxiliary Utilities Used in process, not in

product

Manufacturing

Raw Materials

Recovered heat/ Steam

Water Input

By-products used in other processes

On Site Waste Treatment

Purchased Off-site Energy

Energy Generated On-Site

Fuel

Product

Off Site

Emissions

Steam and/or electricity

Emissions

Fuel

Waste Haz and non-haz

Facility boundary

Emissions

Water Discharge

Non-quantitative Metrics at the Macro level

1. Contribution to National energy security 2. Compatibility with requirement for regional collection,

preprocessing and shipping. 3. Potential for co-use of land and/or production facilities by

other foods and/or feedstocks that have a different production cycle

4. Impact of changing practices that change habitats (e.g. biodiveristy, non-native species, etc.)

5. Compatibility with existing farming practices including financing and risk management.

6. Potential to develop supply “leveling” storage

Workflow, Data,Time & Cost

Smart Manufacturing Open Architecture

Platform

Control & Automation Propriety Optimized

Automation Workflows

Data Partnership Workflow

Orchestration

Toolkits

Sensor Data

Apps Store

Data collection, modeling & Synchronization multi-scale time requirements embedded

Data collection, modeling & synchronization defined by workflow

Single scale time requirement in workflow

Decision

Composability Design to manufacturing Workflow libraries

Separate Data & apps Data to apps paradigm

Generalized Energy Performance and Productivity Metrics Development

• Metrics Experts

• SMLC Collaborators

AIChE, SMLC, NCMS Coordination Team

incorporation of sustainability metrics for energy---Productivity Suite of Metrics

Implement metrics suite and refine as needed for

productivity improvement

Application of generalized

metrics concepts to

broad base of industries

Develop generalized “core” for variety of platforms

Base data from Test Beds and key data

questions

Input from additional stake holder industrial

platforms

‘The Coming Tech Led Boom’ Wall Street Journal, Jan 30, Mark Mills & Julio Ottino

“The Internet is evolving into the "cloud” — a network of thousands of data centers, any one of which

makes a 1990 supercomputer look antediluvian….Astronomical feats of data crunching enable

heretofore unimaginable services and businesses - we are on the cusp of unimaginable new markets.”

Smart manufacturing. This is the first structural shift since Henry Ford launched the economic power

of "mass production. Engineers will soon design and build from the molecular level, optimizing

features and even creating new materials, radically improving quality and reducing waste.”

“The implications of the radical collapse in the cost of wireless connectivity are as big as those

following the dawn of telegraphy/telephony. Coupled with the cloud, the wireless world provides cheap

connectivity, information and processing power to nearly everyone, everywhere – introduces rapid change and great opportunity.”

Cloud Computing & Collaborative Manufacturing

Feedstock Selection

•Petroleum-based

•Natural gas-based

•Bio-based

Next Gen Unit Operations

•Process intensification

•Design optimization

•Skid or modular units

• Innovative separation

Product

•Assure yield

•Minimize waste

•Assure quality and consistency

Traditional CPI

Pharma and Biologics

Automotive

Energy Industries

Food

Modeling Simulations

Practical minimum energy

Sustainability productivity metrics

- Materials

- Water

- Toxics

- Energy

- Land use

Micro, Meso & Macro Levels

Supply Chain

Data Cloud

Security

Project SM

Lifecycle

A Second NNMI under consideration

• Process Intensification

• Systems and Process Intensification Network

• http://processintensification.org/2014

What is Process Intensification (PI)?

*National Science Foundation Workshop on Process Intensification, October 2014, www.processintensification.org, Adapted from European Roadmap of Process Intensification. 2007

Process intensification is a set of often radically innovative principles (“paradigm shift”) in process science, chemistry and equipment design, which can bring significant (more than factor 2) benefits in terms of process and chain efficiency, capital and operating expenses, quality, wastes, process safety, etc*.

Process Intensification is not routine,

incremental process improvement!

http://www.processintensification.org/

Manufacturing and ChemE

Idea

generation

Lead

Definition

Pre –development

Develop-ment

Commercial-ization

Research Push NOT Industrial Pull

DOE has indicated they will announce a Request for Proposals (RFP) for an NNMI on SMART

Another possible NNMI on Process Intensification may

be announced in 2016

• Energy savings 20-80%

• Capital and life cycle savings 20-80%

• Selectivity and yield increase up to >10 times

• Significant process safety increase - reactor volume & inventory of chemicals decreased

10-1000 times + better reaction control

- 25% reduction in safety events

• Efficiency 40% reduction in cycle times

• Execution 10x improvement in time to market in target industries

PI/SM: Reducing Project Risk

34 34

Realized Benefits: PI and SM

• Reduce capital and life cycle cost

• Reduce hazardous material at risk

• Reduce process sampling and characterization points

• Reduce plant footprint

• Enhance worker safety

Chemical Manufacturing Improvements

• Originally adopted to provide intrinsic process safety

• Developed into a tool for project risk reduction

Current Processes

• Less efficient: labor-intensive

• Lower output and productivity

• Lower quality products

• Lower paying unskilled jobs

• Higher risk working conditions

• Higher environmental impact

• Higher production costs

• Rigid, high-volume production

• Slower time-to-market

Intensified Processes

• More efficient: automation-intensive

• Higher output and productivity

• Higher quality products

• Higher paying skilled jobs

• Safer working environment

• Less waste, less resource use

• Lower production costs

• More flexible customization

• Faster time-to-market

Current vs Intensified Processes

PI is often accomplished through chemistry changes with no change in the equipment-For example, the separation efficiency in liquid-liquid extraction can be dramatically increased by changing the properties of the solvent

Elements of Process Intensification

Architecture Process

And Engineering Model

External Network

Secure Network

Machining Furnaces

Microsoft

SQL Server®

File Share

Boundary

Solution Engine® • Aggregation • Analytics • Rules

Solution Engine® • Cloud Connection

REST – HTTPS

Interface

Plant Displays

IR Cameras



Reformer Balancing - Motiva Port Arthur

Thermocouples and Flow Meters


Thermocouples will help validate camera measurements

TC Extractopad TC V-Pad

Flow meters Transmitters

Gas Fired Furnace

• Pre-existing thermocouples and pressure sensors will be utilized to Monitor furnace output in several segregated zones. • Furnace is scheduled back into production January 2016

Hot Forging

• Water Flow Meters and Sensors have been designed in order to detail operational temperatures with in the inside diameter of the • Forge tooling. In addition pre-existing billet temperature thermo camera data will integrated for product heat variation and consistency • M795 Projectile Production has been scheduled for January 2016.

Heat Treatment

• Thermocouple Sensors and Furnace Pressure Sensors have been installed. • Quench Oil Temperature sensors were returned after evaluation and new more

durable sensors have been ordered • Furnace Recuperators (Inkind investment) have been successfully trialed • Production Run for Heat Treat Furnace scheduled for 11/9/15

Integration Status Project Area Status

Furnace Instrumentation In Process

Machine Tool Instrumentation Awaiting MTConnect® Adapter Installation

Plant Server Staged at RTD Offices • Solution Family Installation Complete • Testing Complete OPC/MTConnect® • Await OSI Server Credentials Waiting model integration before plant delivery

Model Development Data Definition • Completing First Iteration of Model Definition • Building Simulation of Data Production on Plant

Server Gathering Complete Tag Point List from Furnaces

Model Testing Await Completion of Definition and Installation

S M L C

O B J E C T I V E S

Develop a standards-based reference architecture based on

industry-driven collaboration with IT suppliers

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

technologies

Lower cost barriers 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

Ensure multi-level cyber security and

protection at a scalable level

Integrate requirements of

small, medium and large enterprises

Facilitate efforts to secure funding through public-

private and private-private partnerships to address priorities

Establish an industry-shared SM Platform that includes an open

architecture software development framework

Implement R&D projects for joint investment and

execution of SM Systems

Operate industry test beds for Smart Manufacturing System

concepts and make them available to companies of all sizes

What is Smart

• Orchestration of standardized decision workflows based on structured adaptation and autonomy

• Applications that can share data, data that can share applications and applications that can connect to applications to achieve horizontal enterprise views and actions

• Actionable data, trust and visibility across supply chain

• In time, in production qualification of materials, products and actions

• In time, in production multi-dimensional (business, operations, supply chain, customer, maintenance, energy) performance and adaptation

• Cross-company operational data to improve

performance

• Evolvable design models in manufacturing

Orchestrated

Decision-making, resilience, autonomy and/or adaptation

With enterprise (end-to-end) contextual data and understanding

While being interoperable, accessible, affordable, secure and reliable

47

Workflow (WfaaS)

WfaaS Integrated with SaaS, PaaS, IaaS

Data-based Workflow Orchestration

Proprietary Workflow

Provisioning

State Tasking

Orchestration

Security Provenance

Application Instances

Application Images (EC2 AMI, OS Glance)

Kepler WFs ISV Software

ComputeCluster

Scratch Scratch Scratch Scratch Scratch Scratch Scratch Scratch

Infiniband

Cloud Compute Layer (EC2, OS Nova, Azure

Compute)

Compute Hardware and Networking

Cloud Object Storage (AWS S3, OS Swift, Azure Storage)

Audit Logs

Actor Data

Access Contr

ol

Actors Provenance Data

Management

Composing Workflows

Data Rights Security

SMLC SM Open Workflow Development & Deployment

User FS

Instance

Workflow Manager Instance

User FS

Instance

Cluster

Instance

Workflow Actor Instance

Streams Manipulators Dashboard

SMLC Hardened Marketplace Buyer WF

Dashboard Buyer

Catalog Portal Apps

Ecommerce Service

Broker

SM Workflow Perspective

Application Images

(Glance)

Object Storage (Swift, Ceph)

OpenStack Cloud Deployment Identity

(Keystone) Virtual Private

Networks (Quantum)

ComputeCluster


Infiniband

Compute Resources (Nova)

Compute Provider Interface (CPI)

ComputeCluster


Infiniband

Shared Storage

Remote Access License

Manager Application Images

IaaS UCLA

Nimbis/Cisco

Rackspace

Amazon,

Azure,

Google

HP

Manipulators Streams Actors Provenance I/O Date Mgm’t Composing Workflows

Data Rights Security

SMLC SM Open Workflow Development & Deployment Dash Board

Marketplace

Validated

Workflows

Company

Workflows

& APPs

R&D

Workflows &

APPs

Marketplace

Commercial

APPs

Open Source

APPs

DOE SM Testbeds (Praxair and GD)

Future SMLC Testbeds

DOE SM Nimbis & UCLA

OpenStack Hosted Platform

SMLC/Nimbis Service Platform

( SM PaaS)

Open

Source

Based

SM Platform Prototype Architecture

IaaS

Providers

Academic,

Open

Source,

Commercial,

Private

Solutions

SMLC Marketplace Buyer WF Dashboard

Buyer Catalog

Portal Apps

Ecommerce Service Broker

Cloud Formation Orchestration

Cloud Resources

DOE SM UCLA & Nimbis

Kepler Workflow Platform

BACK UP

Smart Manufacturing Metrics Research Plan Outline

• Review relevant past and existing metrics • Choose or define metrics of interest • Define boundaries at each organizational level • Define data needs: inputs and outputs of interest* • Define data sources from data needs based on a mapping • Integrate with existing metrics & Information Management

Systems* • Develop the software with testing, verification & validation* • Develop the front-end interfaces, e.g., the dashboard*

* Based on requirements specifications to be developed

SM Metrics Definition and Goals

• “… developing the components and common definitions for an energy productivity metric will draw upon existing and past metric development efforts…will include basic and complementary indicators, ratios, choice of denominators, e.g., mass, revenue, value add, ‘lower is better’, and benchmarks.

• The basic metric is expected to include (components) raw materials, water, net energy, pollutants, toxics, green-house

gases, and societal metrics.” − DOE Application, 12/7/2011

• Generalize metrics from representative testbeds, beginning with: – continuous (steam reforming at Praxair)

– discrete (forging and machining at General Dynamics).

Primary (direct) Impact Issues

Generic for broad application at Meso level

• Cost • Net Greenhouse Gas reduction vs existing • Additional pollution generated

1. Human and ecological toxicity 2. Degradation of air quality (smog, acid rain precursors, &

particulate)

3. Degradation of aquifers and other potable water supplies (nitrification, silt, BOD/COD, & salt)

4. Degradation of surface waters as ecological habitats

5. Degradation of soil or habitats

AIChE Efforts on Commercial Outreach

Facilitate broader acceptance of the energy productivity metrics by small, medium and large manufacturers (AIChE, NCMS, SMLC) ( 10 to 25% complete)

7.5 (Yr. 3) Establish workshops, webinars, and conferences on SM platform for individual industry segments with emphasis on small and medium size organizations (AIChE, NCMS, SMLC) (10 to 25% complete)

Analog for continuous processes (Praxair)

energy to ghg, water performance, sustainability …...smart manufacturing: encouraging paradigm...

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