1. Best Practices for Assembly
Emerging Practices & Technologies for
Smart Assembly
Jim Caie
Vice President
ARC Advisory Group
y p
jcaie@arcweb.com

2. Agenda
The Challenges of Assembly
Assembly P
A bl Practices Research St d
ti R h Study
Assembly Performance Maturity Matrices
Emerging Technologies for Assembly
Smart Assembly – Vision for Discrete Manufacturers
2
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3. The Challenge for Assembly
Assembly Typically Requires Significant Direct Labor
Assembly Operations Remain Difficult to Automate &
Control
Assembly in High Wage Economies is a Difficult
sse y g age co o es s cu
Proposition
Logistics, Regulations, and Market Intelligence Propel a
Business Case to Keep Assembly Close to the Customer
Improvements needed to keep
assembly
assembl close to customer in
c stome
high wage economies
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4. Key Performance Areas to Improve
Cost of Engineering, Equipment, & Operations
Response Time for New Product Innovation
Response Time for Problem Resolution
Reliability of the Process
Leveraging Worker Knowledge & Experience
Safety
Quality
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5. Agenda
The Challenges of Assembly
Assembly Practices Research Study
• People
• Process
• Information
• Technology
• General Motors • Cummins Engine
• Ford • Wright Ind.
Contributing
• P&G • Bosch Rexroth
Companies • John Deere • Danaher Motion
• Motorola • Comua
• Boeing
• Rolls-Royce
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6. Research Findings & Analysis
Assembly Practices : PEOPLE
Desired Self Manage Own (55.6%) Desired
Work
(37.0%)
Current
Current
Resolve Assembly (66.6%)
Problems
(40.7%)
(82.1%)
Team
Workers (70.4%)
(29%)
Support Continuous
Improvement Initiatives
(48.1%)
(48 1%)
(17.9%)
Individual
Workers Only Execute Specific (37.0%)
(71%)
Assembly Tasks
(70.3%)
10 20 30 40 50 60 70 80 90 100 10 20 30 40 50 60 70 80 90 100
Percent of Respondents Percent of Respondents
Organization of W k
O i i f Work Worker Roles
Many jobs will be redesigned to Workers will focus more on
accommodate teams in the value added roles like trouble
future shooting and decision making
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7. Research Findings & Analysis
Assembly Practices : PEOPLE
(10.9%) Desired
Virtual in addition
to Performance
Current
C t
Oriented Training
(40.5%)
Performance
Oriented Training
(19.3%)
(35.1%)
(35 1%)
Task & Equipment
Training
(50.9%)
On-The-Job (13.5%)
Training
(29.8%)
10 20 30 40 50 60 70 80 90 100
Percent of Respondents
Training
Training will be more performance
oriented and virtual methods will
enhance t i i
h training
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8. Research Findings & Analysis
Assembly Practices : PROCESS
Agile Assembly Cells (34.3%) (59.3%)
Intelligent, Flexible
with Major Supplier Desired Assembly Automation
Feeding Operations (7.7%) (12.0%)
Current Desired
Agile Assembly Cells (25.7%) Flexible Assembly (29.6%) Current
with Validated Automation
Feeding Operations (15.4%) (16.0%)
(34.3%) (11.1%)
Short Assembly Line Semi-flexible Assembly
with Validated Feeding Automation
(26.9%)
(26 9%) (48.0%)
(48 0%)
Operations
Long Assembly Line with (5.7%) Inflexible Assembly
Few Feeding Sub-lines Automation
(50.0%) (24.0%)
10 20 30 40 50 60 70 80 90 100 10 20 30 40 50 60 70 80 90 100
Percent of Respondents Percent of Respondents
Physical Assembly Assembly
Architecture There will be more intelligent,
Trend will be towards shorter flex flexible automation to improve
lines/agile cells and more supplier responsiveness, productivity, and
operations in customer plants reliability
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9. Research Findings & Analysis
Assembly Practices : PROCESS
Predominately Kitting & (13.1%) Desired
Intelligent, Agile (61.6%)
Automated Delivery to
Automated Conveyance (3.0%)
(9.4%) Point-of-Use Current
Desired
Most Bulk Containers (56.5%)
Flexible, Automated (30.7%)
Current Directly to Point-of-Use
Conveyance (15.1%)
(9.4%)
Half Bulk Containers (30.4%)
(7.7%)
Semi-flexible, from Central Storage to
Automated C
A t t d Conveyance Point-of-Use,
Point of Use Half (21.3%)
(21 3%)
(34.4%) Directly to Point-of-Use
Most Bulk Containers
Manual Conveyance from Central Storage to
Point-of-Use (60.6%)
(46.8%)
10 20 30 40 50 60 70 80 90 100
10 20 30 40 50 60 70 80 90 100
Percent of Respondents
Percent of Respondents
Conveyance Part/Material Delivery
Trend is toward more intelligent, There will be more kitting and
flexible, automated conveyance more delivery of parts/material
directly to point-of use
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10. Research Findings & Analysis
Assembly Practices : INFORMATION
Portable HMIs, PDAs, & (53.3%)
Easy Access to Real (100.0%)
Role Base Mfg Portals
Time, Actionable (2.7%)
Information (27.0%)
Desired
Stationary HMIs (20.0%)
Fairly Easy Access to Current
Timely, Meaningful (37.8%)
Information (28.0%) Desired
(23.4%)
Current
Somewhat Difficult Electronic Charts &
Access to Timely Marques (29.7%)
(29.0%)
(29 0%)
Meaningful Information
(3.3%)
Difficult Access to Timely, Manual Charts &
Meaningful Information Notes (29.8%)
(16.0%)
10 20 30 40 50 60 70 80 90 100 10 20 30 40 50 60 70 80 90 100
Percent of Respondents Percent of Respondents
Worker Access to Device Types to Access
Information Information
Trend is easier access to More portable communication
information to enable workers devices will enable workers to
to leverage their knowledge be more mobile
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11. Research Findings & Analysis
Assembly Practices : INFORMATION
Intelligent Tracking (25.7%)
Collaborative, Intelligent (92.6%)
Production Management (Vision)
System (PMS) (4.7%)
(46.3%)
Tracking via RFID (46.1%)
Analytic PMS (scheduling, (4.3%)
Desired
block & starved, etc.) (11.6%)
(10.0%) Desired
Current
Current (20.5%)
(3.1%) Tracking via
Basic PMS
(Monitoring & Alarms) Barcodes
(21.5%) (44.2%)
(44 2%)
(7.7%)
No PMS Manual Tracking
(22.2%) (39.5%)
10 20 30 40 50 60 70 80 90 100 10 20 30 40 50 60 70 80 90 100
Percent of Respondents Percent of Respondents
Production Management Part/Material Tracking
Systems (PMS) The use of more intelligent
Future collaborative, intelligent PMS tracking devices will help evaluate
will ensure the schedule gets
g condition of parts and material
executed effectively & efficiently being tracked
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12. Research Findings & Analysis
Assembly Practices : TECHNOLOGY
Intelligent Safety (71.4%)
Extensive Use for (61.1%) Devices Utilized
Optimization & Validation
of Process, Equip & (6.5%)
(15.6%)
Controls Design
Desired Un-obtrusive Safety (28.6%) Desired
Frequent Use for (27.8%)
Analysis & Validation of Devices Mostly Used
(25.0%) Current (19.4%) Current
Process & Equip Design
Moderate use for Process (11.1%) Both Obtrusive &
Feasibility & Basic Design Unobtrusive Safety
(31.2%) Devices Used (41.9%)
Very Limited Use of DM Only Obtrusive Safety
Tools (28.2%) Devices Used (32.2%)
10 20 30 40 50 60 70 80 90 100 10 20 30 40 50 60 70 80 90 100
Percent of Respondents Percent of Respondents
Digital Manufacturing (DM) Safety
Increased use of DM will enable The use of more unobtrusive and
validation without physical builds intelligent safety devices will
enable much more i t
bl h interaction
ti
between people and automation
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© ARC Advisory Group

13. Research Findings & Analysis
Assembly Practices : TECHNOLOGY
Intelligent, Self (69.2%) Intelligent, Automated (60.0%)
Prognostic Devices Adaptive Control
(6.5%)
Desired
(23.1%) Moderate Electronic (35.0%)
Integrated, Real-Time
Device Diagnostics Current Adaptive Control
(36.1%) (29.0%) Desired
(5.0%) Current
(7.7%)
Local Device Limited Manual
Diagnostics (30.5%) Adaptive Control (35.5%)
Very Limited Device No Adaptive
Diagnostics (33.4%) Control (29.0%)
10 20 30 40 50 60 70 80 90 100 10 20 30 40 50 60 70 80 90 100
Percent of Respondents Percent of Respondents
Device Diagnostics Adaptive Control
More intelligent, integrated More intelligent, automated
real-time diagnostics will adaptive control will increase
dramatically improve
y p productivity and quality
manufacturing reliability
13
© ARC Advisory Group

14. Agenda
The Challenges of Assembly
Assembly Practices Research Study
Assembly Performance Maturity Matrices
• Leaders
• Competitors
• Followers
Emerging Technologies for Assembly
Smart Assembly – Vision for Discrete Manufacturers
14
© ARC Advisory Group

15. Performance Maturity Matrix
Assembly Practices - People
Leader Competitor Follower
Focus Many Teams, Some Mostly Individual Individual Workers
Knowledge Workers Workers, Some Teams
Worker Execute, Check, Execute, Check & Execute Assembly
responsibilities Rework, Maintain & Rework Tasks
Improve
Incentives Extensive – Team, Moderate – Some for Very Limited - Only
Knowledge & Company/Team Fixed Hourly Wages
Flexibility Performance
Training Performance Task & Equipment On the Job Training
Oriented Training Training
Safety Monitored Power Electronic Safety Safety SOPs/Equip
(control reliable) Devices & Physical Safety
Systems Devices
15
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16. Performance Maturity Matrix
Assembly Practices - Process
Leader Competitor Follower
Structure of Assembly Cells Short Assembly Lines Long Assembly
Physical (with validated feeding Lines
Process operations)
Amount of Moderate Automation Limited Automation No Automation
Automation (11 – 30%) < 10%
Flexibility of Flexible Automation Semi–Flexible Inflexible
Assembly Automation Automation
Automation
Conveyance Flexible, Automated Semi-Flexible, Manual Conveyance
Conveyance (AGVs) Automated Conveyance
Error Proofing Electronic and Manual Manual EP within Work End of Line Error
(EP) EP within Work Station Proofing
Station
Maintenance Predictive Preventive Reactive
Material Both Kits and Bulk Some Bulk Containers Un-sequenced Bulk
Delivery Containers Mostly Delivered Directly to Containers
Delivered Directly to Point of Use Delivered to Central
Point of Use Storage
Use of Lean Extensive Use – Moderate Use –Mostly Very Limited Use
Manufacturing Institutionalized Contracted
and Six Sigma
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17. Performance Maturity Matrix
Assembly Practices - Information
Leader Competitor Follower
IT/Control Mostly Open Supplier No Standards
Standards Standards Proprietary
Standards
Part/Material RFID Barcode Manual
Tracking
Ease of Access to Fairly Easy – Somewhat Difficult Very Difficult -
Information Electronic Real-time – Some Electronic Mostly Acquired
Information Capability, But Not from People
Available (mostly Real-time and
actionable) Actionable
Data Visibility Portable HMIs and Electronic Charts Manual Charts
Methods Some PDAs (Marques), and Audio Signals
Stationary HMIs
Production Manufacturing Electronic Data Manual Charts
Management Execution Systems Acquisition and and Notes
System Visibility
Knowledge Capture Systematic Some Organized Unorganized –
and Distribution Knowledge Electronic Limited
Processes with Capability to Knowledge
Electronic Capability Capture/Distribute Manually
Knowledge Captured and
Distributed
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18. Performance Maturity Matrix
Assembly Practices - Technology
Leader Competitor Follower
Effectiveness of Di it l
Eff ti f Digital High Optimization
Hi h – O ti i ti Moderate – O l
M d t Only Very Limited -
V Li it d
Manufacturing (DM) and Validation of for Process Tools Hard to Use
Tools Critical Process and Feasibility and
Equipment Designs Basic Design
Device Diagnostics
i i i Real-time, Electronic
l l Non Real-time
l Very Limited
d
and Integrated and Manually
Checked
Adaptive Control Real-time, Electronic Manual, Non Real- Very Limited
and Integrated time
Wireless Capability Real-time Production Sensor Only Person to
Information Information Person
Interaction of People
I i f P l Mostly U
M l Un-obtrusive
b i Some Unobtrusive
S U b i Obtrusive S f
Ob i Safety
and Automation Safety Devices Safety Devices Devices Enabling
Enabling Moderate Enabling Limited Very Limited
Interaction Interaction Interaction
18
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19. Agenda
The Challenges of Assembly
Assembly Practices Research Study
Assembly Performance Maturity Matrices
bl f i i
Emerging Technologies for Assembly
Smart Assembly – Vision for Discrete Manufacturers
Smart
Assembly
Workshop
Participants
P ti i t
19
© ARC Advisory Group

20. Emerging Technology Enabling
Smart Assembly
Topic From To
Automation Manual assembly Optimal balance of people
& automation
Safety Obtrusive safety devices Safe, intelligent robots &
between worker & robot effectors
Adaptive Control Sporadically deployed Self optimizing, learning
systems processes, equip & toolsl
Diagnostics Basic device diagnostics Self diagnostic, prognostic
devices and systems
Motoman 13-axis Dual-Arm
Knowledge Ad-hoc methods to Comprehensive Assembly Robot
Management capture knowledge Knowledge Management
Systems
Quality Expensive, add-on error Automatic error proofing
proofing systems Next generation
Virtual Optimization & Virtual models becoming Automatic synchronization assembly capability
Validation
V lid ti irrelevant with ti
i l t ith time of models with reality
f d l ith lit to
t more effectively
ff ti l
Information & Control Partially open, scalable Totally open, scalable and efficiently utilize
Architecture
people, automation,
Wireless Networks Information Information & Control and information to
dramatically improve
d ti ll i
competitiveness.
20
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21. Key Attributes of Smart Assembly
Empowered, Knowledgeable People
Automated, dexterous, intelligent assembly equipment
Collaboration
Re configurable/re programmable
Re-configurable/re-programmable
Model and data driven
Capable of learning
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22. Technology Roadmaps
Smart Assembly
Intelligent, flexible assembly
processes, equipment, tools
admaps
Pervasive and persistent
e as e a d pe s ste t
ogy Roa
virtual capability
Technolo
Actionable eal time
A tionable real-time data
Infrastructure:
Standards and interoperability
22
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23. Intelligent, Flexible Assembly Processes,
Equipment, and Tools
Intelligent, agile assembly cells
Intelligent, safe cooperative robots
I t lli t f ti b t
Intelligent, agile conveyance
Automatic,
Automatic intelligent error proofing
Re-configurable software and hardware
Elimination of “hard” restrictive safety barriers
hard
Modular, low cost, re-usable
23
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24. Accurate, Easy-to-use, Pervasive and
Persistent Virtual Capability
Collaborative systems engineering
Optimized/validated design before production
Virtual launch of factory
Emulation of changes before deployment
Elimination of physical builds for validation
Synchronization of virtual with real
y
Capability to easily design-in Smart
Assembly attributes into processes &
equipment and virtually validate the results.
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25. Real-time, Actionable Data
for Man and Machine
Wireless, web-enabled monitoring and prognostics
Self 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 context
g
25
© ARC Advisory Group

26. Integrated Information and Control Architecture,
Business Processes and Standards
Open standards
Global
Gl b l common information & control architecture
i f ti t l hit t
Service oriented architecture
“Plug and Play” hardware and software
g y
Interoperable systems for data exchange
Strategic Engineering
Interoperability Challenge
Migrate to globally
common, open systems
26
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27. Performance Maturity Matrix
Smart Assembly
People Processes Information Technology
Empowered Intelligent,Highly Open Standards Virtual Optimization
Knowledge Automated Agile & Validation of
Teams Assembly Cells & Process, Equipment
Conveyance & Controls Designs
Virtual & Designed –in
g Easy Access to
y Intelligent, Self
g ,
Performance Lean, Safety, Real Time, Prognostic Devices
Oriented Training Automation, & Actionable & Automatic
Reliability Information Adaptive Control
Optimal Balance Reliability Collaborative Intelligent,
Intelligent Safe
of People & Centered Operations Robots &
Automation Manufacturing Management End-Effectors
Systems
Monitored Power Material Kits & Comprehensive Wireless Control
(control reliable) Containers Knowledge
Systems & Automatically Management
Un-obtrusive Delivered Systems
Safety D i
S f t Devices Directly t
Di tl to
Point-of-use
27
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28. Technology & Deployment Roadmaps
Smart Assembly
ps
Intelligent, flexible assembly
oadmap
processes, equipment, tools
tries
Pervasive and persistent
e as e a d pe s ste t
ology Ro
utomotive
e
Aerospace
e
Othe Indust
virtual capability
er
Actionable eal time
A tionable real-time data
Au
Techno
A
Infrastructure:
Standards and interoperability
Use cases; Implementation/Deployment Roadmaps
28
© ARC Advisory Group

29. Thank You.
For more information, contact the author at
jcaie@arcweb.com or visit our web pages at
www.arcweb.com
www arcweb com
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© ARC Advisory Group