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5. Operations Scheduling

5. Operations Scheduling. Scheduling Flow. Scheduling Decisions. Operations Scheduling. Specify time-phased activities and control job-order progress Jobs are activities to be done and machines (work centers) process jobs Single machine problem Parallel machine problem Flow shop problem

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5. Operations Scheduling

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  1. 5. Operations Scheduling

  2. Scheduling Flow

  3. Scheduling Decisions

  4. Operations Scheduling • Specify time-phased activities and control job-order progress • Jobs are activities to be done and machines (work centers) process jobs • Single machine problem • Parallel machine problem • Flow shop problem • Job shop problem

  5. Day Work Center Monday Tuesday Wednesday Thursday Friday Metalworks Job 349 Job 350 Mechanical Job 349 Job 408 Electronics Job 408 Job 349 Painting Job 295 Job 408 Job 349 Processing Unscheduled Center not available Gantt Chart Example

  6. Scheduling Criteria • Makespan • Time required to complete a production schedule, or time required to manufacture all jobs • Total (average) flow time • Total (average) amount of time jobs spend in the system • Utilization • Total processing time / Total flow time • Total (average) lateness • Total(average) amount of time jobs are completed beyond its promised delivery date

  7. Scheduling Rules • FCFS (First come, first served) • The first job arriving is processed first • SPT (Shortest processing time) • The job with the SPT is processed first • EDD (Earliest due date) • The job with the EDD is processed first • LPT (Longest processing time) • The job with the LPT is processed first • CR (Critical ratio) – can be dynamic • Jobs are scheduled in order of increasing ratioof time remaining to required work time remaining

  8. An Example (Single Machine)

  9. An Example (continued) • FCFS: A-B-C-D-E • SPT: B-D-A-C-E • EDD: B-A-D-C-E • LPT: E-C-A-D-B • CR: A-B-C-D-E

  10. An Example (continued)

  11. Comparison of Scheduling Rules • No one scheduling rule excels on all criteria • SPT minimizes flow time, but moves long jobs to the end, which may result in dissatisfied customers • FCFS does not do especially well (or poorly) on any criteria but is perceived as fair by customers • EDD often minimizes lateness related criteria

  12. Two Machine Flow Shop • Johnson’s algorithm minimizes makespan • List all jobs and times for each work center • Choose the job with the shortest activity time. If that time is in the first work center, schedule the job first. If it is in the second work center, schedule the job last • Once a job is scheduled, it is eliminated from the list • Repeat above steps working toward the center of the sequence

  13. An Example

  14. Time 0 3 10 20 28 33 WC 1 B E D C A WC 2 B E D C A Time 0 1 3 5 7 9 10 11 12 13 17 19 21 22 23 25 27 29 31 33 35 A B E D C An Example (continued)

  15. More Than Two Machine Flow Shop • Each job is processed by each machine (work center) exactly once • Very difficult to solve; a heuristic approach is necessary • Reduce multiple machines to two machines and apply Johnson’s algorithm • Solve m-1 sub-problems for an m machine shop by increasing number of ‘real’ machines for the 1st ‘artificial’ machine and decreasing it for the 2nd one.

  16. An Example

  17. Job Shop (6 job 4 machine example)

  18. Limitations of Rule-Based Dispatching • Rules do not look upstream or downstream; idle resources and bottleneck resources in other departments may not be recognized • Rules do not look beyond due dates • Scheduling is dynamic and rules need to be revised to adjust to changes in process, equipment, product mix, etc.

  19. Scheduling Service Employees With Cyclical Scheduling • Objective is to meet staffing requirements with the minimum number of workers • Schedules need to be smooth and keep personnel happy • Many techniques exist from simple algorithms to complex linear programming solutions • Cyclical scheduling -- Identify two consecutive days with the lowest total requirements and assign these as days off

  20. An Example

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