Abstract
This study addresses a multi-period part selection problem for flexible manufacturing systems in which processing times are controllable. The problem is to determine the set of parts and their processing times while satisfying the processing time and the tool magazine capacities in each period of a planning horizon. The objective is to minimize the sum of processing, earliness/tardiness, subcontracting and tool costs. Practical considerations such as available tool copies and tool lives are also considered. An integer programming model is developed, and two-phase heuristics are proposed in which an initial solution is obtained by a greedy heuristic under initial processing times and then it is improved using local search methods while adjusting processing times. Computational experiments were done on a number of test instances, and the results are reported.
Highlights
Flexible manufacturing system (FMS) is an automated manufacturing system that consists of numerical control machines and an automated material handling/storage system, which are controlled by a computer control system
This study focuses on a multi-period part selection problem with controllable processing times, which is the problem of determining a set of parts and their processing times in each period of a planning horizon
The problem is to determine the set of parts to be produced in each period of a planning horizon and their processing times while satisfying the constraints on processing time capacity, tool magazine capacity, tool copies and tool lives
Summary
Flexible manufacturing system (FMS) is an automated manufacturing system that consists of numerical control machines and an automated material handling/storage system, which are controlled by a computer control system. An FMS is capable of processing various part types simultaneously with higher utilization. Alternatively called batching in the literature, is the problem of selecting the parts to be produced during the upcoming planning period. Most previous studies on FMS part selection propose single-period models that determine a set of parts to be produced simultaneously during an upcoming period. See Hwang and Shogan [1], Kim and Yano [2] and Bilge et al [3] for examples. To obtain better solutions over the planning horizon with multiple periods, some articles extend the single-period models to multi-period ones. See Stecke and Toczylowski [4] and Lee and Kim [5] for examples
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