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An optimization tool for operational tolerances allocation, work in process inventory minimization, and machines assignment in a discrete part manufacturing environment

机译:一个优化工具,用于分配操作公差,最小化流程中的库存以及离散零件制造环境中的机器分配

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摘要

In the last two decades, many researchers have addressed the superior system performance resulted from the integration of process planning and scheduling functions. However, most of the published solution methods in this field fall short in three accounts. First, while integrating with scheduling, they ignore the checking of process planning feasibility with respect to tolerances allocation. Thus, operational tolerances may stackup beyond the blue print tolerances making the process plans infeasible. Second, they ignore the machines capabilities during the integration modeling which make these solution models practically inapplicable. Third, they focus on time consideration, such as makespan or lateness, and do not consider manufacturing cost related to operations-machines assignment. This paper presents an innovative model for the integration of process planning and scheduling in a job-shop environment. The model simultaneously serves three purposes: allocating operational tolerances while minimizing its manufacturing cost, minimizing the work in process inventory, and figuring the operation-machine assignments. The preemptive-goal programming method is used to solve the proposed multiobjective non-linear mixed integer model, and an implementation example is presented to demonstrate the effectiveness of the proposed modeling approach.
机译:在过去的二十年中,许多研究人员已经解决了由于集成了流程计划和调度功能而带来的卓越系统性能。但是,该领域中大多数已发布的解决方法在三个方面都不够。首先,在与计划集成时,他们忽略了有关公差分配的过程计划可行性检查。因此,操作公差可能超出蓝图公差,从而使工艺计划不可行。其次,他们忽略了集成建模过程中的机器功能,这使得这些解决方案模型实际上不适用。第三,他们着眼于时间因素,例如制造期或延迟,而不考虑与作业机分配相关的制造成本。本文提出了一种创新模型,用于在车间环境中集成过程计划和计划。该模型同时具有三个目的:分配操作公差,同时最大程度地降低制造成本,最小化过程库存工作,以及确定操作机器分配。采用先占目标规划方法求解所提出的多目标非线性混合整数模型,并给出一个实现实例,说明所提出的建模方法的有效性。

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