2020
DOI: 10.48084/etasr.3903
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Integrated Preventive Maintenance Scheduling Model with Redundancy for Cutting Tools on a Single Machine

Abstract: In this paper, we present an integrated multi-objective framework of a single machine for a single cutting tool problem. Our maintenance policy is based on performing minimal repairs in case of a minor failure and Preventive Maintenance (PM) to avoid a major failure that results in the replacement of the tool. This framework allows simultaneous optimization of the two conflicting time and cost objectives. A redundant system is proposed as a part of the model to assist the production line under a major failure.… Show more

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Cited by 13 publications
(7 citation statements)
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References 28 publications
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“…Constraints ( 18) and ( 19) state that the vehicle can be dispatched if it is assigned to DC . Constraints (20) to (23) are the mathematical representation of Figure 1. Constraints ( 24) to ( 25) are variables restrictions.…”
Section: ⏟⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏟⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞...mentioning
confidence: 99%
See 1 more Smart Citation
“…Constraints ( 18) and ( 19) state that the vehicle can be dispatched if it is assigned to DC . Constraints (20) to (23) are the mathematical representation of Figure 1. Constraints ( 24) to ( 25) are variables restrictions.…”
Section: ⏟⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏟⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞...mentioning
confidence: 99%
“…The crowding distance method, on the other hand, preserves the diversity of the solutions by calculating the dispersion of any two neighboring solutions in each front. These two procedures shape the Pareto front at each iteration [22,23]. After generating an initial parent population ( 0 ), all non-dominated individuals are sorted.…”
Section: Non-dominated Sorting Genetic Algorithm II (Nsga-ii)mentioning
confidence: 99%
“…• Preventive maintenance can be used as an effective solution for the problem of cutting tool life in manufacturing since it helps manufacturing operators to avoid major failures that result in the replacement and change of tools [19].…”
Section: Step Four: Improvementioning
confidence: 99%
“…The genetic algorithm is a stochastic optimization technique inspired by the process of natural selection, which is widely applied to solve different classes of NP-Hard problems [15,16,17,18]. GA maintains a population of candidate solutions through the selective procedure.…”
Section: Modified Genetic Algorithmmentioning
confidence: 99%