Controlling a manufacturing system efficiently

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Controlling a manufacturing system efficiently

• IE450
• Fall 2005
• Dr. Richard A. Wysk

2
Agenda

• Present a simple system
• Show state of the art in scheduling
• Define implementation specifics
• Example problem

3
Readings

• Chapter 7 Factory Physics

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ExerciseReadiness Assessment Test A.K.A. RAT

• For homework, prepare a Gantt chart of parts
  flow for the 2 CNC machine and 1 robot system
  that was discussed as part of the robot slides
  (prepared before class)
• Two parts are made where each part goes from
  machine 1 machine 2
• For part 1 processing times are 2 and 4
  minutes.
• For part 2 processing times are 3 and 2.5
  minutes
• What is the cycle time for the part?
• Open Book / Open Notes

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ExerciseReadiness Assessment Test A.K.A. RAT

• AS A class, take 3 minutes to answer the
  following questions
• Do you think that all of the Gantt Charts the
  same?
• Is there a best way to set-up an operation? Why?
• Closed Book / Closed Notes

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IllustrateControl Requirements
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Resource AcquisitionFor Real-time Control State
preconditions/prerequisites
MH tasks are represented explicitly like MP
tasks Resource management is significantly complex
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Some Observations about this Perspective

• Generic -- applies to any system
• Other application specifics
• Parts
• Number
• Routing
• Buffers (none in our system)

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System and scheduling specifics

• Flow shop
• Two machine system
• Optimal formulation

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Johnsons Algorithm (1954)

1. List all jobs
2. Choose shortest processing time
3. If it belongs to the 1st machine, schedule it at
   the 1st machine in first available slot
4. If it belongs to the 2nd machine, schedule it at
   the 2nd machine in the last available slot
5. Cross out that job
6. If last job, end
7. Go to step 2

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Johnsons Algorithm (1954)

• Optimal sequence P1 - P3 - P4 - P2
• Is the schedule actually optimal in reality?

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Traditional schedule vs. Realistic schedule
(blocking effects)
1
3
4
2
M1
1
3
4
2
M2
Make-span 25
M1
Can not begin 4 until 3 moves
1
3
4
2
M2
1
3
4
2
Material Handling
Make-span 29
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Actual optimal sequence
M1
1
3
4
2
M2
1
3
4
2
Optimum by Johnsons algorithm
Make-span 29
M1
1
2
3
4
M2
1
2
3
4
Actual optimum
Make-span 28
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Things to be considered for higher fidelity of
scheduling

• Deadlocking and blocking related issues must be
  considered
• Material handling must be considered
• Buffers (and buffer transport time) must be
  considered

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Jacksons Algorithm (1956)

1. List all jobs as M1 M2 , M2 M1, M1, M2
2. Schedule M1 M2 , M2 M1 using Johnsons
   algorithm
3. Order M1 M2 , M2 M1 jobs
4. Place M1, M2 arbitrarily between M1 M2 , M2
   M1

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Jacksons Algorithm (1956)

• Optimal sequence
• M1 P1 - P2 - P3
• M2 P3 - P4 - P1
• Is the schedule actually optimal in reality?

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Schedule Implementation

• If no buffers exist, it is impossible to
  implement the schedule as the optimum schedule by
  Jacksons rule
• Even if buffers exist, several better schedules
  may exist including the following schedule
• M1 P1 - P2 - P3
• M2 P1 - P3 - P4

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Simulation specifics

• Very detailed simulation models that emulate the
  steps of parts through the system must be
  developed.
• Caution must be taken to insure that the model
  behaves properly.
• The simulation allocates resources (planning) and
  sequences activities (scheduling).

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Why Acquire (seize) together?To avoid deadlock
P2 (M1-M2)
P1 (M1-M2)
M2
M1
part, being processed
part, done
Legend

• If we acquire robot and machine separately
• the robot will be acquired by the P2
• a deadlock situation will occur
• If we acquire robot and machine at the same time
• the robot will not be acquired until M2 becomes
  free

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Conclusion

• Control is the implementation of schedules
• Schedules dictate much of the system efficiency
• Implementation is not that hard