Determination of aggregate preventive maintenance programs using production schedules

Sridhar, S.

doi:10.1016/0360-8352(88)90028-9

Cited by 14 publications

(1 citation statement)

References 2 publications

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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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Section: Notationmentioning

confidence: 99%

Integrating Preventive Maintenance Planning and Production Scheduling for a Single Machine

2005

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References

2016

Machine Tool Reliability

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Boolean-controlled systems via receding horizon and linear programing

Bauso

2009

Math. Control Signals Syst.

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We consider dynamic systems controlled by boolean signals or decisions. We show that in a number of cases, the receding horizon formulation of the control problem can be solved via linear programming by relaxing the binary constraints on the control. The idea behind our approach is conceptually easy: a feasible control can be forced by imposing that the boolean signal is set to one at least one time over the horizon. We translate this idea into constraints on the controls and analyze the polyhedron of all feasible controls. We specialize the approach to the stabilizability of switched and impulsively-controlled systems.

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Determination of aggregate preventive maintenance programs using production schedules

Cited by 14 publications

References 2 publications

Integrating Preventive Maintenance Planning and Production Scheduling for a Single Machine

Integrating Preventive Maintenance Planning and Production Scheduling for a Single Machine

References

Boolean-controlled systems via receding horizon and linear programing

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