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A new approach towards integrated cell formation and inventory lot sizing in an unreliable cellular manufacturing system

机译:在不可靠的蜂窝制造系统中实现集成单元形成和库存批量确定的新方法

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摘要

This paper presents a comprehensive mathematical model for integrated cell formation and inventory lot sizing problem. The proposed model seeks to minimize cell formation costs as well as the costs associated with production, while dynamic conditions, alternative routings, machine capacity limitation, operations sequences, cell size constraints, process deterioration, and machine breakdowns are also taken into account. The total cost consists of machine procurement, cell reconfiguration, preventive and corrective repairs, material handling (intra-cell and inter-cell), machine operation, part subcontracting, finished and unfinished parts inventory cost, and defective parts replacement costs. With respect to the multiple products, multiple process plans for each product and multiple routing alternatives for each process plan which are assumed in the proposed model, the model is combinatorial. Moreover, unreliability conditions are considered, because moving from "in-control" state to "out-of-control" state (process deterioration) and machine breakdowns make the model more practical and applicable. To conquer the breakdowns, preventive and corrective actions are adopted. Finally, a Particle Swarm Optimization (PSO)-based meta-heuristic is developed to overcome NP-completeness of the proposed model.
机译:本文提出了一个综合的数学模型,用于解决单元格形成和库存批量确定的问题。所提出的模型力求使单元形成成本以及与生产相关的成本最小化,同时还考虑了动态条件,替代路线,机器容量限制,操作顺序,单元尺寸约束,过程恶化和机器故障。总成本包括机器采购,单元重组,预防性和纠正性维修,物料搬运(单元内和单元间),机器操作,零件分包,成品和未完成的零件库存成本以及有缺陷的零件更换成本。对于所提出的模型中假设的多个产品,每个产品的多个过程计划以及每个过程计划的多个工艺路线选择,该模型是组合的。此外,考虑了不可靠条件,因为从“处于控制中”状态变为“失控”状态(过程恶化)和机器故障使模型更加实用和适用。为了克服故障,采取了预防和纠正措施。最后,开发了基于粒子群优化(PSO)的元启发式算法,以克服所提出模型的NP完整性。

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