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A genetic algorithm approach for production scheduling with mould maintenance consideration

机译:考虑模具维护的生产调度的遗传算法

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The traditional approach for maintenance scheduling concerns single-resource (machine) maintenance during production which may not be sufficient to improve production system reliability as a whole. Besides, in the literature many researchers schedule maintenance activities periodically with fixed maintenance duration. However, in a real manufacturing system maintenance activities can be executed earlier and the maintenance duration will become shorter since less time and effort are required. A practical example is that in a plastic production system, the proportion of machine-related downtime is even lower than mould-related downtime. The planned production operations are usually interrupted seriously because of the mismatch among the maintenance periods between injection machine and mould. In this connection, this paper proposes to jointly schedule production and maintenance tasks of multi-resources in order to improve production system reliability by reducing the mismatch among various processes. To integrate machine and mould maintenance tasks in production, this paper attempts to model the production scheduling with mould scheduling (PS-MS) problem with time-dependent deteriorating maintenance schemes. The objective of this paper is to propose a genetic algorithm approach to schedule maintenance tasks jointly with production jobs for the PS-MS problem, so as to minimise the makespan of production jobs.
机译:维护计划的传统方法涉及生产期间的单资源(机器)维护,这可能不足以从整体上提高生产系统的可靠性。此外,在文献中,许多研究人员以固定的维护时间定期安排维护活动。然而,在实际的制造系统中,由于需要较少的时间和精力,因此可以更早地执行维护活动,并且维护时间将缩短。一个实际的例子是,在塑料生产系统中,与机器相关的停机时间所占比例甚至低于与模具相关的停机时间。由于注塑机和模具之间的维护周期不匹配,计划的生产操作通常会严重中断。为此,本文提出了共同调度多资源的生产和维护任务,以通过减少各种过程之间的不匹配来提高生产系统的可靠性。为了将机器和模具维护任务集成到生产中,本文尝试使用模具调度(PS-MS)问题对模型进行生产调度,该模型具有时间依赖性的恶化维护方案。本文的目的是提出一种遗传算法方法,与PS-MS问题一起计划生产任务的维护任务,以最小化生产任务的工期。

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