Controlling a manufacturing system efficiently IE450 Fall 2005 Dr. Richard A. Wysk

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

Readings Chapter 7 – Factory Physics

Exercise Readiness Assessment Test A.K.A. RAT For homework 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

Exercise Readiness Assessment Test A.K.A. RAT AS A class 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

Illustrate Control Requirements Task Number Task Name 1Pick L 2Put M1 3Process 1 4Pick M1 5Put M2 6Process 2 7Pick M2 8Put UL M1M2 R L UL

Resource Acquisition:For Real-time Control State preconditions/prerequisites MH tasks are represented explicitly like MP tasks Resource management is significantly complex Task Number Task Name M1M2R 1Pick L  2Put M1  3Process 1  4Pick M1  5Put M2  6Process 2  7Pick M2  8Put U  

Some Observations about this Perspective Generic -- applies to any system Other application specifics –Parts Number Routing Buffers (none in our system)

System and scheduling specifics Flow shop Two machine system Optimal formulation

Johnson’s Algorithm (1954) 1.List all jobs 2.Choose shortest processing time 1.If it belongs to the 1 st machine, schedule it at the 1 st machine in first available slot 2.If it belongs to the 2 nd machine, schedule it at the 2 nd machine in the last available slot 3.Cross out that job 4.If last job, end 5.Go to step #2

Johnson’s Algorithm (1954) Optimal sequence: P1 - P3 - P4 - P2 Is the schedule actually optimal in reality?

Traditional schedule vs. Realistic schedule (blocking effects) Make-span: 25 M1 M Make-span: 29 M1 M2 + Material Handling Can not begin 4 until 3 moves

Actual optimal sequence Make-span: 29 M1 M2 Optimum by Johnson’s algorithm Make-span: 28 M1 M2 Actual optimum

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

Jackson’s Algorithm (1956) 1.List all jobs as M 1 – M 2, M 2 – M 1, M 1, M 2 2.Schedule M 1 – M 2, M 2 – M 1 using Johnson’s algorithm 3.Order M 1 – M 2, M 2 – M 1 jobs 4.Place M 1, M 2 arbitrarily between M 1 – M 2, M 2 – M 1

Jackson’s Algorithm (1956) Optimal sequence: –M1: P1 - P2 - P3 –M2: P3 - P4 - P1 Is the schedule actually optimal in reality?

Schedule Implementation If no buffers exist, it is impossible to implement the schedule as the optimum schedule by Jackson’s rule Even if buffers exist, several better schedules may exist including the following schedule: –M1: P1 - P2 - P3 –M2: P1 - P3 - P4

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).

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

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