Best practices for assembly j caie arc orlando 2008

Best Practices for AssemblyBest Practices for AssemblyBest Practices for AssemblyEmerging Practices & Technologies for

Smart Assembly

Best Practices for AssemblyEmerging Practices & Technologies for

Smart AssemblySmart AssemblySmart Assembly

Jim CaieVice President

ARC Advisory Groupy [email protected]

AgendaAgenda

The Challenges of Assembly

A bl P ti R h St dAssembly Practices Research Study

Assembly Performance Maturity Matrices

Emerging Technologies for AssemblyEmerging Technologies for Assembly

Smart Assembly – Vision for Discrete Manufacturers

2© ARC Advisory Group

The Challenge for AssemblyThe Challenge for Assembly

Assembly Typically Requires Significant Direct LaborAssembly Operations Remain Difficult to Automate & ControlAssembly in High Wage Economies is a Difficult sse y g age co o es s a cuPropositionLogistics, Regulations, and Market Intelligence Propel a Business Case to Keep Assembly Close to the CustomerBusiness Case to Keep Assembly Close to the Customer

Improvements needed to keepassembl close to c stome inassembly close to customer in

high wage economies


Key Performance Areas to ImproveKey Performance Areas to Improve

Cost of Engineering, Equipment, & OperationsResponse Time for New Product InnovationResponse Time for New Product InnovationResponse Time for Problem ResolutionReliability of the ProcessLeveraging Worker Knowledge & ExperienceSafetyQualityQuality


AgendaAgenda


Assembly Practices Research StudyAssembly Practices Research Study

• People

• Process

• Information

• Technology

• General Motors

• Ford

• P&G

• Cummins Engine

• Wright Ind.

• Bosch RexrothContributing

• P&G

• John Deere

• Motorola

• Boeing

• Bosch Rexroth

• Danaher Motion

• Comua

Companies


• Boeing

• Rolls-Royce

Research Findings & AnalysisAssembly Practices : PEOPLEResearch Findings & AnalysisAssembly Practices : PEOPLE

Current

Desired

Current

DesiredSelf Manage Own Work

(55.6%)

(37.0%)

Team Workers

(82.1%)

(29%) Support Continuous Improvement Initiatives

Resolve Assembly Problems

(48 1%)

(70.4%)

(40.7%)

(66.6%)

Individual Workers

(17.9%)

(71%) Only Execute Specific Assembly Tasks

Improvement Initiatives

(70.3%)

(37.0%)

(48.1%)

O i i f W k Worker Roles

Percent of Respondents10 20 30 40 50 60 70 80 90 100


Organization of WorkMany jobs will be redesigned to accommodate teams in the future

Worker RolesWorkers will focus more on value added roles like trouble shooting and decision making


future shooting and decision making

Research Findings & AnalysisAssembly Practices : PEOPLEResearch Findings & AnalysisAssembly Practices : PEOPLE

C t

DesiredVirtual in addition to Performance

(10.9%)

Current

Performance Oriented Training

to Performance Oriented Training

(19.3%)

(35 1%)

(40.5%)

On-The-Job Training

Task & Equipment Training

(29.8%)

(35.1%)

(50.9%)

(13.5%)


TrainingTraining will be more performance oriented and virtual methods will

h t i i


enhance training

Research Findings & AnalysisAssembly Practices : PROCESSResearch Findings & AnalysisAssembly Practices : PROCESS

Current

DesiredAgile Assembly Cells with Major Supplier Feeding Operations

(34.3%)

(7.7%)Desired

Intelligent, Flexible Assembly Automation

(59.3%)

(12.0%)Current

Short Assembly Line with Validated Feeding

Agile Assembly Cells with Validated Feeding Operations

(25.7%)

(15.4%)

(34.3%)

(26 9%)

Current

Semi-flexible Assembly Automation

Flexible Assembly Automation

(29.6%)

(11.1%)

(16.0%)

(48 0%)

Long Assembly Line with Few Feeding Sub-lines

with Validated Feeding Operations (26.9%)

(5.7%)

(50.0%)

Inflexible Assembly Automation

Automation (48.0%)

(24.0%)

Physical Assembly



Assembly ArchitectureTrend will be towards shorter flex lines/agile cells and more supplier operations in customer plants

There will be more intelligent, flexible automation to improve responsiveness, productivity, and reliability


operations in customer plants reliability

Research Findings & AnalysisAssembly Practices : PROCESSResearch Findings & AnalysisAssembly Practices : PROCESS

Intelligent, Agile Automated Conveyance

(61.6%)

(9.4%) Current

DesiredPredominately Kitting & Automated Delivery to Point-of-Use

(13.1%)

(3.0%)

Current

Desired

Semi-flexible, A t t d C

Flexible, Automated Conveyance

(30.7%)

(9.4%)

(7.7%) Half Bulk Containers from Central Storage to Point of Use Half

Most Bulk Containers Directly to Point-of-Use

(15.1%)

(21 3%)

(30.4%)

(56.5%)

Manual Conveyance

Automated Conveyance (34.4%)

(46.8%)

Most Bulk Containers from Central Storage to Point-of-Use

Point-of-Use, Half Directly to Point-of-Use

(21.3%)

(60.6%)

Conveyance



Part/Material DeliveryConveyanceTrend is toward more intelligent, flexible, automated conveyance

Part/Material DeliveryThere will be more kitting and more delivery of parts/material directly to point-of use


Research Findings & AnalysisAssembly Practices : INFORMATIONResearch Findings & AnalysisAssembly Practices : INFORMATION

Easy Access to Real Time, Actionable Information

(100.0%)

(27.0%)Desired

Portable HMIs, PDAs, & Role Base Mfg Portals

(53.3%)

(2.7%)

Current

Desired

Somewhat Difficult Access to Timely

Fairly Easy Access to Timely, Meaningful Information

(29 0%)

(28.0%)

Current

Electronic Charts & Marques

Stationary HMIs (20.0%)

(37.8%)

(23.4%)

(29.7%)

10 20 30 40 50 60 70 80 90 100

Difficult Access to Timely, Meaningful Information

Access to Timely Meaningful Information

(29.0%)

(16.0%)

10 20 30 40 50 60 70 80 90 100

Manual Charts & Notes

Marques

(3.3%)

(29.8%)

Worker Access to Information



Device Types to Access InformationInformation

Trend is easier access to information to enable workers to leverage their knowledge

InformationMore portable communication devices will enable workers to be more mobile


to leverage their knowledge

Research Findings & AnalysisAssembly Practices : INFORMATIONResearch Findings & AnalysisAssembly Practices : INFORMATION

Intelligent Tracking (Vision)

(25.7%)

(4.7%)

Collaborative, Intelligent Production Management System (PMS) (46.3%)

(92.6%)

Current

Desired

Tracking via Barcodes

Tracking via RFID (46.1%)

(20.5%)

(11.6%)

(44 2%)

Current

Desired

Basic PMS (Monitoring & Alarms)

Analytic PMS (scheduling, block & starved, etc.)

(4.3%)

(3.1%)

(10.0%)

Manual Tracking

Barcodes (44.2%)

(7.7%)

(39.5%)No PMS

(Monitoring & Alarms)

(22.2%)

(21.5%)

Part/Material Tracking



Production Management Part/Material TrackingThe use of more intelligent tracking devices will help evaluate condition of parts and material

Production Management Systems (PMS)Future collaborative, intelligent PMS will ensure the schedule gets


being trackedg

executed effectively & efficiently

Research Findings & AnalysisAssembly Practices : TECHNOLOGYResearch Findings & AnalysisAssembly Practices : TECHNOLOGY

Extensive Use for Optimization & Validation of Process, Equip & Controls Design

(61.1%)

(15.6%)

Intelligent Safety Devices Utilized

(71.4%)

(6.5%)

Current

Desired

Moderate use for Process Feasibility & Basic Design

Frequent Use for Analysis & Validation of Process & Equip Design

Controls Design

(27.8%)

(25.0%)

(11.1%)

Current

Desired

Both Obtrusive & Unobtrusive Safety

Un-obtrusive Safety Devices Mostly Used

(28.6%)

(19.4%)

Very Limited Use of DM Tools

Feasibility & Basic Design(31.2%)

(28.2%)Only Obtrusive Safety Devices Used

Unobtrusive Safety Devices Used (41.9%)

(32.2%)



Digital Manufacturing (DM)Increased use of DM will enable validation without physical builds

SafetyThe use of more unobtrusive and intelligent safety devices will

bl h i t ti


enable much more interaction between people and automation

Research Findings & AnalysisAssembly Practices : TECHNOLOGYResearch Findings & AnalysisAssembly Practices : TECHNOLOGY

Intelligent, Self Prognostic Devices

(69.2%) Intelligent, Automated Adaptive Control

(60.0%)

(6.5%)

Current

Desired

Local Device

Integrated, Real-Time Device Diagnostics

(23.1%)

(36.1%)

(7.7%) Current

Desired

Limited Manual

Moderate Electronic Adaptive Control

(35.0%)

(29.0%)

(5.0%)

Very Limited Device Diagnostics

Local Device Diagnostics (30.5%)

(33.4%)No Adaptive Control

Limited Manual Adaptive Control (35.5%)

(29.0%)

Device Diagnostics Adaptive Control



Device DiagnosticsMore intelligent, integrated real-time diagnostics will dramatically improve

Adaptive ControlMore intelligent, automated adaptive control will increase productivity and quality


y pmanufacturing reliability

productivity and quality

AgendaAgenda


Assembly Practices Research StudyAssembly Practices Research Study

Assembly Performance Maturity Matrices

• Leaders

• Competitors

• Followers

Emerging Technologies for Assembly

Smart Assembly – Vision for Discrete Manufacturers


Performance Maturity MatrixAssembly Practices - People Performance Maturity MatrixAssembly Practices - People

Leader Competitor Follower

Focus Many Teams, Some Knowledge Workers

Mostly Individual Workers, Some Teams

Individual Workers

Worker Execute, Check, Execute, Check & Execute Assembly responsibilities Rework, Maintain &

Improve Rework Tasks

Incentives Extensive – Team, Knowledge &

Moderate – Some for Company/Team

Very Limited - Only Fixed Hourly Wages

Flexibility Performance

Training Performance Oriented Training

Task & Equipment Training

On the Job Training

Safety Monitored Power (control reliable) Systems

Electronic Safety Devices

Safety SOPs/Equip & Physical Safety Devices


Performance Maturity MatrixAssembly Practices - Process Performance Maturity MatrixAssembly Practices - Process


Structure of Physical

Assembly Cells Short Assembly Lines (with validated feeding

Long Assembly LinesPhysical

Process (with validated feeding

operations) Lines

Amount of Automation

Moderate Automation (11 – 30%)

Limited Automation < 10%

No Automation

Flexibility of Assembly Automation

Flexible Automation Semi–Flexible Automation

Inflexible Automation

Conveyance Flexible, Automated Conveyance (AGVs)

Semi-Flexible, Automated Conveyance

Manual ConveyanceConveyance (AGVs) Automated Conveyance

Error Proofing (EP)

Electronic and Manual EP within Work

Station

Manual EP within Work Station

End of Line Error Proofing

Maintenance Predictive Preventive ReactiveMaintenance Predictive Preventive Reactive

Material Delivery

Both Kits and Bulk Containers Mostly

Delivered Directly to Point of Use

Some Bulk Containers Delivered Directly to

Point of Use

Un-sequenced Bulk Containers

Delivered to Central Storage


Use of Lean Manufacturing and Six Sigma

Extensive Use – Institutionalized

Moderate Use –Mostly Contracted

Very Limited Use

Performance Maturity MatrixAssembly Practices - Information Performance Maturity MatrixAssembly Practices - Information


IT/Control Standards

Mostly Open Standards

Supplier Proprietary

No Standards Standards Standards Proprietary

Standards

Part/Material Tracking

RFID Barcode Manual

Ease of Access to Information

Fairly Easy – Electronic Real-time

Information Available (mostly

actionable)

Somewhat Difficult – Some Electronic Capability, But Not

Real-time and Actionable

Very Difficult - Mostly Acquired

from People

Data Visibility Methods

Portable HMIs and Some PDAs

Electronic Charts (Marques),

Stationary HMIs

Manual Charts and Audio Signals

Production Management

Manufacturing Execution Systems

Electronic Data Acquisition and

Manual Charts and NotesManagement

System Execution Systems Acquisition and

Visibility and Notes

Knowledge Capture and Distribution

Systematic Knowledge

Processes with

Some Organized Electronic

Capability to

Unorganized –Limited

Knowledge


Processes with Electronic Capability

Capability to Capture/Distribute

Knowledge

KnowledgeManually

Captured and Distributed

Performance Maturity MatrixAssembly Practices - Technology Performance Maturity MatrixAssembly Practices - Technology


Eff ti f Di it l Hi h O ti i ti M d t O l V Li it dEffectiveness of Digital Manufacturing (DM) Tools

High – Optimization and Validation of

Critical Process and Equipment Designs

Moderate – Only for Process

Feasibility and Basic Design

Very Limited -Tools Hard to Use

i i i l l l dDevice Diagnostics Real-time, Electronic and Integrated

Non Real-timeand Manually

Checked

Very Limited

Adaptive Control Real-time, Electronic Manual, Non Real- Very Limited and Integrated time

Wireless Capability Real-time Production Information

Sensor Information

Only Person to Person

I i f P l M l U b i S U b i Ob i S fInteraction of Peopleand Automation

Mostly Un-obtrusive Safety Devices

Enabling Moderate Interaction

Some Unobtrusive Safety Devices

Enabling Limited Interaction

Obtrusive Safety Devices Enabling

Very Limited Interaction


AgendaAgendaThe Challenges of Assembly

Assembly Practices Research Study

bl f i iAssembly Performance Maturity Matrices

Emerging Technologies for Assembly

Smart Assembly – Vision for Discrete ManufacturersSmart Assembly Vision for Discrete Manufacturers

Smart Assembly Workshop

P ti i tParticipants


Emerging Technology EnablingSmart AssemblyEmerging Technology EnablingSmart Assembly

Topic From To

Automation Manual assembly Optimal balance of peopleAutomation Manual assembly Optimal balance of people & automation

Safety Obtrusive safety devices between worker & robot

Safe, intelligent robots & effectors

Adaptive Control Sporadically deployed Self optimizing, learning & l

Motoman 13-axis Dual-Arm Assembly Robot

systems processes, equip & tools

Diagnostics Basic device diagnostics Self diagnostic, prognostic devices and systems

Knowledge Management

Ad-hoc methods to capture knowledge

Comprehensive Knowledge Management

Next generation assembly capability t ff ti l

Management capture knowledge Knowledge Management Systems

Quality Expensive, add-on error proofing systems

Automatic error proofing

Virtual Optimization & V lid ti

Virtual models becoming i l t ith ti

Automatic synchronization f d l ith lit to more effectively

and efficiently utilize people, automation, and information to

d ti ll i

Validation irrelevant with time of models with reality

Information & Control Architecture

Partially open, scalable Totally open, scalable

Wireless Networks Information Information & Control


dramatically improve competitiveness.

Key Attributes of Smart AssemblyKey Attributes of Smart Assembly

Empowered, Knowledgeable PeopleAutomated, dexterous, intelligent assembly equipmentCollaborationRe-configurable/re-programmableRe configurable/re programmableModel and data drivenCapable of learning


Technology Roadmaps Smart AssemblyTechnology Roadmaps Smart Assembly

Intelligent, flexible assembly

adm

aps

Intelligent, flexible assembly processes, equipment, tools

Pervasive and persistent

ogy

Roae as e a d pe s ste t

virtual capability

A tionable eal time data

Tech

noloActionable real-time data

Infrastructure:Standards and interoperability


Intelligent, Flexible Assembly Processes, Equipment, and ToolsIntelligent, Flexible Assembly Processes, Equipment, and Tools

Intelligent, agile assembly cells

I t lli t f ti b tIntelligent, safe cooperative robots

Intelligent, agile conveyance

Automatic intelligent error proofingAutomatic, intelligent error proofing

Re-configurable software and hardware

Elimination of “hard” restrictive safety barriersElimination of hard restrictive safety barriers

Modular, low cost, re-usable


Accurate, Easy-to-use, Pervasive and Persistent Virtual CapabilityAccurate, Easy-to-use, Pervasive and Persistent Virtual Capability

Collaborative systems engineering

Optimized/validated design before productionOptimized/validated design before production

Virtual launch of factory

Emulation of changes before deploymentEmulation of changes before deployment

Elimination of physical builds for validation

Synchronization of virtual with realy

Capability to easily design-in Smart Assembly attributes into processes &Assembly attributes into processes &

equipment and virtually validate the results.


Real-time, Actionable Data for Man and MachineReal-time, Actionable Data for Man and Machine

Wireless, web-enabled monitoring and prognostics

Self diagnosisSelf diagnosis

Portable HMIs & PDAs for workers

Decision support for optimized maintenance/recovery

Collaborative operations management systems

Comprehensive knowledge management systems

Easy access to accurate information in the right contextg


Integrated Information and Control Architecture, Business Processes and StandardsIntegrated Information and Control Architecture, Business Processes and Standards

Open standards

Gl b l i f ti & t l hit tGlobal common information & control architecture

Service oriented architecture

“Plug and Play” hardware and softwareg y

Interoperable systems for data exchange

Strategic Engineering

Migrate to globally

Interoperability ChallengeInteroperability Challenge

Migrate to globally common, open systems


Performance Maturity Matrix Smart AssemblyPerformance Maturity Matrix Smart Assembly

People Processes Information Technology

Empowered Knowledge

Intelligent,Highly Automated Agile

Open Standards Virtual Optimization & Validation ofKnowledge

Teams Automated Agile Assembly Cells &

Conveyance

& Validation of Process, Equipment & Controls Designs

Virtual & Designed –in Easy Access to Intelligent, Self Performance

Oriented Training

gLean, Safety, Automation, &

Reliability

yReal Time, Actionable Information

g ,Prognostic Devices

& Automatic Adaptive Control

Optimal Balance Reliability Collaborative Intelligent SafeOptimal Balance of People & Automation

Reliability Centered

Manufacturing

Collaborative Operations

Management Systems

Intelligent, Safe Robots &

End-Effectors

Monitored Power (control reliable)

Systems & Un-obtrusive

S f t D i

Material Kits & Containers

Automatically Delivered Di tl t

Comprehensive Knowledge

Management Systems

Wireless Control


Safety Devices Directly to Point-of-use

Technology & Deployment Roadmaps Smart AssemblyTechnology & Deployment Roadmaps Smart Assembly

psIntelligent, flexible assembly

oad

mapIntelligent, flexible assembly

processes, equipment, tools

Pervasive and persistent e e trie

s

olo

gy R

oe as e a d pe s ste tvirtual capability

A tionable eal time data uto

motive

Aer

osp

ace

er I

ndust

Tech

noActionable real-time data

Infrastructure:

Au A

Oth

e

Standards and interoperability


Use cases; Implementation/Deployment Roadmaps

Thank You.Thank You.For more information, contact the author at [email protected] or visit our web pages at

www arcweb com


www.arcweb.com

Best practices for assembly j caie arc orlando 2008

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