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Preventive Maintenance
Principles
SPL 7.2
Scott Couzens, LFM ’06
Scott Hiroshige, LFM ‘06
Presentation for:
Summer 2004
i
Erik Smith, LFM ’03 – Intel Corporation
ESD.60 – Lean/Six Sigma Systems
MIT Leaders for Manufacturing Program (LFM)
These materials were developed as part of MIT's ESD.60 course on "Lean/Six Sigma Systems." In some cases,
the materials were produced by the lead instructor, Joel Cutcher-Gershenfeld, and in some cases by student teams
working with LFM alumni/ae. Where the materials were developed by student teams, additional nputs from the
faculty and from the technical instructor, Chris Musso, are reflected in some of the text or in an appendix
6/ 2© [ /
Special Thanks to:
¾ DNS Employees:
¾Roger Nuffer
¾David Villareal
¾Marcus Hunsaker
¾ Intel Employees:
¾Jonathan Matthews
¾David Latham
¾Eli Sorenson
¾Danny Miller
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
6/ 3© [ /
Overview
¾ Learning Objectives
¾
types of maintenance
activities
¾ Appreciation of the benefits of
preventive maintenance
¾ Understanding of lean
princi
preventive maintenance
schedule
¾ Awareness of specific
challenges to implementing
preventive maintenance
¾ Session Design (20-30 min.)
¾ Part I: Introduction and Learning
Objectives (1-2 min.)
¾ Part II: Key Concept or Principle
Defined and Explained (3-5 min.)
¾ Part III: Exercise or Activity
Based on Field Data that
Illustrates the Concept or
Principle (7-10 min.)
¾ Part IV: Common “Disconnects,”
Relevant Measures of Success,
and Potential Action
Assignment(s) to Apply Lessons
Learned (7-10 min.)
¾ Part V: Evaluation and
Concluding Comments (2-3 min.)
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
Familiarity with the different
ples for designing a
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
6/ 4© [ /
Types of Maintenance
¾ Breakdown Maintenance:
¾ Waiting until equipment fails before repairing or servicing it
¾ Preventive Maintenance (PM):
¾
cleaning, or replacing parts to prevent sudden failure
¾ (Predictive) On-line monitoring of equipment in order to use
important/expensive parts to the limit of their serviceable life
¾ Corrective or Predictive Maintenance:
¾ Improving equipment and its components so that preventive
maintenance can be carried out reliably
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
(Time-based or run-based) Periodically inspecting, servicing,
6/ 5© [ /
Benefits of Preventive Maintenance
¾ “…the cost of breakdown maintenance is usually much
greater than preventive maintenance.” 1
¾ Preventive maintenance…
¾ Keeps equipment in good condition to prevent large problems
¾ Extends the useful life of equipment
¾ Finds small problems before they become big ones
¾ Is an excellent training tool for technicians
¾ Helps eliminate rework/scrap and reduces process variability
¾ Keeps equipment safer
¾ Parts stocking levels can be optimized
¾ Greatly reduces unplanned downtime
1
/ l
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
http://www.prenhall.com divisions/bp/app/russel cd/PROTECT/CHAPTERS/CHAP15/HEAD01.HTM
6/ 6© [ /
The Manufacturing Game
¾ Similar to the Beer Game
¾ Simulates a typical plant with three roles:
¾ Operations Manager
¾ Maintenance Manager
¾ Spare Parts Stores Manager
¾ Each round, participants make decisions such as:
¾ Which equipment to take down for PMs
¾ How to allocate maintenance resources
¾ How many spare parts to order
¾ Revenue, cost, output, uptime, inventory are recorded
i
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
Source: Business Dynam cs: Systems Thinking and Modeling for a Complex World,
Sterman, John D., 2000.
6/ 7© [ /
The Manufacturing Game Results
¾ Teams who follow a cost-minimization strategy (reactive
maintenance policies) are able to keep costs low for a
uptime falling and costs rising.
¾ Teams who follow a preventive maintenance strategy
initially find higher costs and reduced uptime as
equipment is taken offline for planned maintenance.
Soon, however, these teams begin to greatly outperform
teams following a cost-minimization strategy.
i
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
while. However, as defects build up they find their
Source: Business Dynam cs: Systems Thinking and Modeling for a Complex World,
Sterman, John D., 2000.
6/ 8© [ /
When Does PM Make Sense?
¾ PM makes sense when the cost of doing PM is less than the
cost of NOT doing PM.
¾ CDoingPM =
and man-hours consumed in PM, potential for making
things worse, etc.)
¾ CNotDoingPM =
makes no difference in preventing the failure), materials
and man-hours spent repairing equipment, loss of
etc.)
PM makes sense if C < C
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
f(hours of not running equipment, loss in employee
morale from doing PM instead of “real work”, materials
f(cost of losing/reworking a failed batch (unless PM
equipment lifetime, loss in employee morale from NOT
doing PM, reduced employee familiarity with equipment,
DoingPM NotDoingPM
6/ 9© [ /
Optimizing a PM Schedule
¾ Question:
¾ If a certain piece of production equipment requires ~10 hours of
preventive maintenance per week, how should those 10 hours
be scheduled?
¾ Answer:
¾ In a 24x7 manufacturing operation, it is typically better to
perform the ~10 hours of activities in several smaller periods of
time, for instance 5 PM activities that take ~2 hours each
¾ Duration and variability in preventive maintenance are key
factors in whether equipment will be able to maintain a steady
flow of output
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
6/ 10© [ /
PM Durations: Simulation 1
¾
hours (85% availability)
0
50
100
150
200
250
300
350
400
450
()
Drop Page Fields Here
io
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
Simulation of equipment with a 10 hour average PM duration, std dev 20
Trend of Queues for the Toolset
83 88 99 109114119125133139147152157162167172177182187192198203211216221226231236241246267
Days into Simulation
AverageQueueLength#ofLots
1 - 10h mean, 2 CV
Avg Queuelength
Day
Scenar
Data from a simulation run at Intel Fab 11X.
6/ 11© [ /
PM Durations: Simulation 2
¾
hours (85% availability)
0
50
100
150
200
250
300
350
400
450
83 88 93
()
Drop Page Fields Here
io
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
Simulation of equipment with a 5 hour average PM duration, std dev 10
Trend of Queues for a Toolset
98 103 108 113 118 125 137 155 164 194 201 213 228 233 244 259 264 277 285
Days into Simulation
AverageQueueLength#ofLots
2 - 5h mean, 2 CV
Avg Queuelength
Day
Scenar
Data from a simulation run at Intel Fab 11X.
6/ 12© [ /
PM Durations: Simulation 3
¾
hours (85% availability)
0
50
100
150
200
250
300
350
400
450
84 91 102 125 148 160 173 196 209 225 238 273 279 287
()
Drop Page Fields Here
io
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
Simulation of equipment with a 2 hour average PM duration, std dev 4
Trend of Queues for a Toolset
116 138 230 261
Days into Simulation
AverageQueueLength#ofLots
3 - 2h mean, 2 CV
Avg Queuelength
Day
Scenar
Data from a simulation run at Intel Fab 11X.
6/ 13© [ /
PM Durations: Simulation 4
¾
hours (85% availability)
0
50
84
l
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
Simulation of equipment with a 2 hour average PM duration, std dev 6
Trend of Queues for a Toolset
100
150
200
250
300
350
400
450
98 112 117 122 127 133 138 143 148 153 158 163 168 173 178 183 188 193 204 222 242 258 264 275 286 291
Days into Simulation
AverageQueueLength(#ofLots)
4 - 2h mean, 3 CV
Drop Page Fie ds Here
Avg Queuelength
Day
Scenario
Data from a simulation run at Intel Fab 11X.
6/ 14© [ /
PM Durations: Why they matter
¾ For the exact same availability on a piece of equipment:
¾ Shorter PM durations mean a difference in days of lot
cycle time!
¾
¾ Regardless of the mean, performing PMs inconsistently
is functionally equivalent to consistently having much
longer downtime durations
57564) µ=2h, σ=6h
883) µ=2h, σ=4h
52382) µ=5h, σ=10h
63561) µ=10h, σ=20h
StdDev QueueLengthAvg QueueLengthSimulation
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
Each day of factory cycle time = millions of $$
Data from simulations run at Intel Fab 11X.
6/ 15© [ /
The “Waddington Effect”
¾ First observed by C.H. Waddington during WWII for
British aircraft maintenance
¾ Background theory: unscheduled downtime should
be a random phenomenon
¾ If all unscheduled downtime events are plotted with
respect to the last PM, there should not be any
pattern evident
¾ A pattern of increased unscheduled downtime
immediately following PM’s is a “Waddington
Effect”
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
Information from a presentation given at Intel Fab 11X.
6/ 16© [ /
The “Waddington Effect”
0
10
20
30
40
50
60
70
0.5 1 1.5 2 2.5 3 3.5 4 4.5
¾
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
"Waddington Effect" Report - Trend of Unscheduled Downtime
Frequency Following PMs for the last 12 work weeks
Days since End of Last PM
#ofUnscheduledDownEvents
REPAIR
QUAL
OUT OF CNTRL
# of Unsched Downs
Days Since PM
Event_Type
Impact of Waddington Effect = 1.4% Availability
Data from a set of production tools at Intel Fab 11X.
6/ 17© [ /
Challenges to Implementing
Preventive Maintenance
¾ Technical Factors
¾ Breakdown maintenance
preventive maintenance
in the short-term
¾ Under-trained technicians
can cause more damage
¾ Social Factors
¾ Organizations are
output goals, etc.)
¾
always well understood
¾ The focus on minimizing
organizational
performance
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
is typically cheaper than
than they prevent
frequently structured in
ways that promote local
optimums (cost, shiftly
The benefits of preventive
maintenance are not
maintenance costs has to
shift to maximizing overall
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
6/ 18© [ /
Concluding Comments
¾ Performing preventive maintenance is almost always the best
long-term strategy to maintain equipment
¾ PM scheduling and strategy are keys to maximizing output
while reducing work-in-process inventory
¾ Due to short-term cost increases and local optimums, there are
barriers to implementing a preventive maintenance strategy at
some plants
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
6/ 19© [ /
Appendix: Instructor’s Comments and Class
Discussion for 7.2
¾ PM is an important tool for establishing stability
necessary for other lean elements:
¾Andon, 5s, etc.
¾ How do you escape the crisis management
whirlpool?
¾Social disconnects:
¾Change the mindset of management, maintenance
group from reaction to prevention
¾May need to be done in steps
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
6/ 20© [ /
Appendix: Instructor’s Guide
•1-2 min17
•Disconnects2-3 min16
•
Game
• i
• Discuss “Waddington Effect”
Exercises/Activities6-15
4-5
1-3
Slide
•
•
Key Concepts3-5 min
•
• iveslearning objectives
2-3 min
Additional Talking PointsTopicTime
9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
Summarize key points of preventive maintenanceConcluding comments
Discuss the difficulties of implementing preventive
maintenance in a reactive maintenance culture
Go through the key learnings of the Manufacturing
Go through a PM optim zation example
7-15 min
Describe the 3 types of maintenance
Explain the benefits of preventive maintenance
Acknowledge contributors to the presentation
Provide an overview of the learning object
Introduction, overview and
Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion

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7 2prevent main

  • 1. Preventive Maintenance Principles SPL 7.2 Scott Couzens, LFM ’06 Scott Hiroshige, LFM ‘06 Presentation for: Summer 2004 i Erik Smith, LFM ’03 – Intel Corporation ESD.60 – Lean/Six Sigma Systems MIT Leaders for Manufacturing Program (LFM) These materials were developed as part of MIT's ESD.60 course on "Lean/Six Sigma Systems." In some cases, the materials were produced by the lead instructor, Joel Cutcher-Gershenfeld, and in some cases by student teams working with LFM alumni/ae. Where the materials were developed by student teams, additional nputs from the faculty and from the technical instructor, Chris Musso, are reflected in some of the text or in an appendix
  • 2. 6/ 2© [ / Special Thanks to: ¾ DNS Employees: ¾Roger Nuffer ¾David Villareal ¾Marcus Hunsaker ¾ Intel Employees: ¾Jonathan Matthews ¾David Latham ¾Eli Sorenson ¾Danny Miller 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
  • 3. 6/ 3© [ / Overview ¾ Learning Objectives ¾ types of maintenance activities ¾ Appreciation of the benefits of preventive maintenance ¾ Understanding of lean princi preventive maintenance schedule ¾ Awareness of specific challenges to implementing preventive maintenance ¾ Session Design (20-30 min.) ¾ Part I: Introduction and Learning Objectives (1-2 min.) ¾ Part II: Key Concept or Principle Defined and Explained (3-5 min.) ¾ Part III: Exercise or Activity Based on Field Data that Illustrates the Concept or Principle (7-10 min.) ¾ Part IV: Common “Disconnects,” Relevant Measures of Success, and Potential Action Assignment(s) to Apply Lessons Learned (7-10 min.) ¾ Part V: Evaluation and Concluding Comments (2-3 min.) 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT Familiarity with the different ples for designing a Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
  • 4. 6/ 4© [ / Types of Maintenance ¾ Breakdown Maintenance: ¾ Waiting until equipment fails before repairing or servicing it ¾ Preventive Maintenance (PM): ¾ cleaning, or replacing parts to prevent sudden failure ¾ (Predictive) On-line monitoring of equipment in order to use important/expensive parts to the limit of their serviceable life ¾ Corrective or Predictive Maintenance: ¾ Improving equipment and its components so that preventive maintenance can be carried out reliably 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion (Time-based or run-based) Periodically inspecting, servicing,
  • 5. 6/ 5© [ / Benefits of Preventive Maintenance ¾ “…the cost of breakdown maintenance is usually much greater than preventive maintenance.” 1 ¾ Preventive maintenance… ¾ Keeps equipment in good condition to prevent large problems ¾ Extends the useful life of equipment ¾ Finds small problems before they become big ones ¾ Is an excellent training tool for technicians ¾ Helps eliminate rework/scrap and reduces process variability ¾ Keeps equipment safer ¾ Parts stocking levels can be optimized ¾ Greatly reduces unplanned downtime 1 / l 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion http://www.prenhall.com divisions/bp/app/russel cd/PROTECT/CHAPTERS/CHAP15/HEAD01.HTM
  • 6. 6/ 6© [ / The Manufacturing Game ¾ Similar to the Beer Game ¾ Simulates a typical plant with three roles: ¾ Operations Manager ¾ Maintenance Manager ¾ Spare Parts Stores Manager ¾ Each round, participants make decisions such as: ¾ Which equipment to take down for PMs ¾ How to allocate maintenance resources ¾ How many spare parts to order ¾ Revenue, cost, output, uptime, inventory are recorded i 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion Source: Business Dynam cs: Systems Thinking and Modeling for a Complex World, Sterman, John D., 2000.
  • 7. 6/ 7© [ / The Manufacturing Game Results ¾ Teams who follow a cost-minimization strategy (reactive maintenance policies) are able to keep costs low for a uptime falling and costs rising. ¾ Teams who follow a preventive maintenance strategy initially find higher costs and reduced uptime as equipment is taken offline for planned maintenance. Soon, however, these teams begin to greatly outperform teams following a cost-minimization strategy. i 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion while. However, as defects build up they find their Source: Business Dynam cs: Systems Thinking and Modeling for a Complex World, Sterman, John D., 2000.
  • 8. 6/ 8© [ / When Does PM Make Sense? ¾ PM makes sense when the cost of doing PM is less than the cost of NOT doing PM. ¾ CDoingPM = and man-hours consumed in PM, potential for making things worse, etc.) ¾ CNotDoingPM = makes no difference in preventing the failure), materials and man-hours spent repairing equipment, loss of etc.) PM makes sense if C < C 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion f(hours of not running equipment, loss in employee morale from doing PM instead of “real work”, materials f(cost of losing/reworking a failed batch (unless PM equipment lifetime, loss in employee morale from NOT doing PM, reduced employee familiarity with equipment, DoingPM NotDoingPM
  • 9. 6/ 9© [ / Optimizing a PM Schedule ¾ Question: ¾ If a certain piece of production equipment requires ~10 hours of preventive maintenance per week, how should those 10 hours be scheduled? ¾ Answer: ¾ In a 24x7 manufacturing operation, it is typically better to perform the ~10 hours of activities in several smaller periods of time, for instance 5 PM activities that take ~2 hours each ¾ Duration and variability in preventive maintenance are key factors in whether equipment will be able to maintain a steady flow of output 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
  • 10. 6/ 10© [ / PM Durations: Simulation 1 ¾ hours (85% availability) 0 50 100 150 200 250 300 350 400 450 () Drop Page Fields Here io 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion Simulation of equipment with a 10 hour average PM duration, std dev 20 Trend of Queues for the Toolset 83 88 99 109114119125133139147152157162167172177182187192198203211216221226231236241246267 Days into Simulation AverageQueueLength#ofLots 1 - 10h mean, 2 CV Avg Queuelength Day Scenar Data from a simulation run at Intel Fab 11X.
  • 11. 6/ 11© [ / PM Durations: Simulation 2 ¾ hours (85% availability) 0 50 100 150 200 250 300 350 400 450 83 88 93 () Drop Page Fields Here io 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion Simulation of equipment with a 5 hour average PM duration, std dev 10 Trend of Queues for a Toolset 98 103 108 113 118 125 137 155 164 194 201 213 228 233 244 259 264 277 285 Days into Simulation AverageQueueLength#ofLots 2 - 5h mean, 2 CV Avg Queuelength Day Scenar Data from a simulation run at Intel Fab 11X.
  • 12. 6/ 12© [ / PM Durations: Simulation 3 ¾ hours (85% availability) 0 50 100 150 200 250 300 350 400 450 84 91 102 125 148 160 173 196 209 225 238 273 279 287 () Drop Page Fields Here io 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion Simulation of equipment with a 2 hour average PM duration, std dev 4 Trend of Queues for a Toolset 116 138 230 261 Days into Simulation AverageQueueLength#ofLots 3 - 2h mean, 2 CV Avg Queuelength Day Scenar Data from a simulation run at Intel Fab 11X.
  • 13. 6/ 13© [ / PM Durations: Simulation 4 ¾ hours (85% availability) 0 50 84 l 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion Simulation of equipment with a 2 hour average PM duration, std dev 6 Trend of Queues for a Toolset 100 150 200 250 300 350 400 450 98 112 117 122 127 133 138 143 148 153 158 163 168 173 178 183 188 193 204 222 242 258 264 275 286 291 Days into Simulation AverageQueueLength(#ofLots) 4 - 2h mean, 3 CV Drop Page Fie ds Here Avg Queuelength Day Scenario Data from a simulation run at Intel Fab 11X.
  • 14. 6/ 14© [ / PM Durations: Why they matter ¾ For the exact same availability on a piece of equipment: ¾ Shorter PM durations mean a difference in days of lot cycle time! ¾ ¾ Regardless of the mean, performing PMs inconsistently is functionally equivalent to consistently having much longer downtime durations 57564) µ=2h, σ=6h 883) µ=2h, σ=4h 52382) µ=5h, σ=10h 63561) µ=10h, σ=20h StdDev QueueLengthAvg QueueLengthSimulation 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion Each day of factory cycle time = millions of $$ Data from simulations run at Intel Fab 11X.
  • 15. 6/ 15© [ / The “Waddington Effect” ¾ First observed by C.H. Waddington during WWII for British aircraft maintenance ¾ Background theory: unscheduled downtime should be a random phenomenon ¾ If all unscheduled downtime events are plotted with respect to the last PM, there should not be any pattern evident ¾ A pattern of increased unscheduled downtime immediately following PM’s is a “Waddington Effect” 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion Information from a presentation given at Intel Fab 11X.
  • 16. 6/ 16© [ / The “Waddington Effect” 0 10 20 30 40 50 60 70 0.5 1 1.5 2 2.5 3 3.5 4 4.5 ¾ 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion "Waddington Effect" Report - Trend of Unscheduled Downtime Frequency Following PMs for the last 12 work weeks Days since End of Last PM #ofUnscheduledDownEvents REPAIR QUAL OUT OF CNTRL # of Unsched Downs Days Since PM Event_Type Impact of Waddington Effect = 1.4% Availability Data from a set of production tools at Intel Fab 11X.
  • 17. 6/ 17© [ / Challenges to Implementing Preventive Maintenance ¾ Technical Factors ¾ Breakdown maintenance preventive maintenance in the short-term ¾ Under-trained technicians can cause more damage ¾ Social Factors ¾ Organizations are output goals, etc.) ¾ always well understood ¾ The focus on minimizing organizational performance 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT is typically cheaper than than they prevent frequently structured in ways that promote local optimums (cost, shiftly The benefits of preventive maintenance are not maintenance costs has to shift to maximizing overall Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
  • 18. 6/ 18© [ / Concluding Comments ¾ Performing preventive maintenance is almost always the best long-term strategy to maintain equipment ¾ PM scheduling and strategy are keys to maximizing output while reducing work-in-process inventory ¾ Due to short-term cost increases and local optimums, there are barriers to implementing a preventive maintenance strategy at some plants 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion
  • 19. 6/ 19© [ / Appendix: Instructor’s Comments and Class Discussion for 7.2 ¾ PM is an important tool for establishing stability necessary for other lean elements: ¾Andon, 5s, etc. ¾ How do you escape the crisis management whirlpool? ¾Social disconnects: ¾Change the mindset of management, maintenance group from reaction to prevention ¾May need to be done in steps 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT
  • 20. 6/ 20© [ / Appendix: Instructor’s Guide •1-2 min17 •Disconnects2-3 min16 • Game • i • Discuss “Waddington Effect” Exercises/Activities6-15 4-5 1-3 Slide • • Key Concepts3-5 min • • iveslearning objectives 2-3 min Additional Talking PointsTopicTime 9/04 --LFM Students] – ESD.60 Lean Six Sigma Systems, LFM, MIT Summarize key points of preventive maintenanceConcluding comments Discuss the difficulties of implementing preventive maintenance in a reactive maintenance culture Go through the key learnings of the Manufacturing Go through a PM optim zation example 7-15 min Describe the 3 types of maintenance Explain the benefits of preventive maintenance Acknowledge contributors to the presentation Provide an overview of the learning object Introduction, overview and Part I: Introduction Part II: Concepts Part III: Application Part IV: Disconnects Part V: Conclusion