A simulation study of sequencing and maintenance decisions in a dynamic job shop

Burton, Jonathan; Banerjee, Avijit; Sylla, Cheickna

doi:10.1016/0360-8352(89)90103-4

Cited by 14 publications

(7 citation statements)

References 5 publications

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“…Largest Buffer to Previous 1,2,or 3 Photo Step(s) (BACK1, BACK2, BACK3): This policy attempts to give priority to a down machine that has a large amount of WIP upstream from it that will be delayed if the machine is down for any length of time. It looks at the amount of WIP between the process step(s) on which the down machine works and the previous photo step(s).…”

Section: A Maintenance Staffing Policiesmentioning

confidence: 99%

“…Burton et al [2] evaluate various maintenance scheduling techniques using a simulation model of a hypothetical job 0894-6507/98$10.00 © 1998 IEEE shop. The authors conclude that maintenance scheduling rules are important, especially when an inefficient job scheduling rule is in use, maintenance resources are scarce, shop congestion is high, or PM tasks are scheduled frequently.…”

Section: Previous Related Workmentioning

confidence: 99%

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Maintenance scheduling and staffing policies in a wafer fabrication facility

Mosley

Teyner²,

Uzsoy

1998

IEEE Trans. Semicond. Manufact.

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We examine how to reduce the adverse effects of machine down time by prioritizing production equipment for attention by a limited number of maintenance personnel. The maintenance scheduling policies use system information to determine which machines are the most critical at a given time. This information includes repair times, queue lengths, due dates, available capacity, and steady-state utilizations. The effects of different staffing levels are also considered. A discrete-event simulation model of a wafer fabrication facility is used to examine the performance of the different policies. Results indicate that the choice of maintenance scheduling policy can significantly affect system performance under restrictive staffing levels. Moreover, factory performance is shown to be sensitive to small changes in staffing level.

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Section: A Maintenance Staffing Policiesmentioning

confidence: 99%

Section: Previous Related Workmentioning

confidence: 99%

Maintenance scheduling and staffing policies in a wafer fabrication facility

Mosley

Teyner²,

Uzsoy

1998

IEEE Trans. Semicond. Manufact.

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“…Likewise, preventive maintenance planning models tend to ignore the potential disruptions in production resulting from PM actions. Those that consider job schedules tend to ignore the possibility of revising a previously-determined production schedule based on machine availability considerations [14], [15].…”

Section: Notationmentioning

confidence: 99%

Integrating Preventive Maintenance Planning and Production Scheduling for a Single Machine

2005

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Summary & Conclusions-Preventive maintenance planning, and production scheduling are two activities that are inter-dependent but most often performed independently. Considering that preventive maintenance, and repair affect both available production time, and the probability of machine failure, we are surprised that this inter-dependency seems to be overlooked in the literature. We propose an integrated model that coordinates preventive maintenance planning decisions with single-machine scheduling decisions so that the total expected weighted completion time of jobs is minimized. Note that the machine of interest is subject to minimal repair upon failure, and can be renewed by preventive maintenance. We investigate the value of integrating production scheduling with preventive maintenance planning by conducting an extensive experimental study using small scheduling problems. We compare the performance of the integrated solution with the solutions obtained from solving the preventive maintenance planning, and job scheduling problems independently. For the problems studied, integrating the two decision-making processes resulted in an average improvement of approximately 2% and occasional improvements of as much as 20%. Depending on the nature of the manufacturing system, an average savings of 2% may be significant. Certainly, savings in this range indicate that integrated preventive maintenance planning, and production scheduling should be focused on critical (bottleneck) machines. Because we use total enumeration to solve the integrated model for small problems, we propose a heuristic approach for solving larger problems. Our analysis is based on minimizing total weighted completion time; thus, both the scheduling, and maintenance problems favor processing shorter jobs in the beginning of the schedule. Given that due-date-based objectives, such as minimizing total weighted job tardiness, present more apparent trade-offs & conflicts between preventive maintenance planning, and job scheduling, we believe that integrated preventive maintenance planning & production scheduling is a worthwhile area of study.

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“…The model determines the optimum number of operators to hire and train under the assumption of just-in-time, zero-inventory production. Burton et al [2] use a simulation model to evaluate several maintenance scheduling rules involving workload, shop capacity, job sequencing, and preventive maintenance policy in a dynamic job shop. They expect that a sufficient maintenance workforce would considerably improve job shop operation.…”

Section: Literature Reviewmentioning

confidence: 99%

A Simulation Approach for Stochastic Employee Days-Off Scheduling

Alfares¹

2007

International Journal of Modelling and Simulation

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This paper presents a simulation approach for employee days-off scheduling when the daily labour demands are random variables.A simulation model is constructed, and a case study application of the proposed approach is described. The model recognizes limited staff availability, stochastic workload variability, and policy restrictions on the choice of employee work schedules. The model has been successfully applied in the days-off scheduling of a multicraft maintenance workforce of an oil and gas pipelines department.Without increasing the number or cost of employees, the model recommended alternative days-off assignments that are expected to reduce throughput times for maintenance work orders by an average of 25%.

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A simulation study of sequencing and maintenance decisions in a dynamic job shop

Cited by 14 publications

References 5 publications

Maintenance scheduling and staffing policies in a wafer fabrication facility

Maintenance scheduling and staffing policies in a wafer fabrication facility

Integrating Preventive Maintenance Planning and Production Scheduling for a Single Machine

A Simulation Approach for Stochastic Employee Days-Off Scheduling

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