TY - JOUR
T1 - A multiobjective evaluation of flexible manufacturing system loading heuristics
AU - Chen, Yung Jung
AU - Askin, Ronald
N1 - Funding Information:
A Flexible Manufacturing System (FMS) is a set of computer-numerically controlled machine tools connected by an automatic material handling system and all controlled by a central computer system. FMSs are typically intended for batch manufacture of a variety of medium demand part types. Versatile machines, capable of performing a wide range of manufacturing operations with quick tooling and instruction changeovers, allow simultaneous production of multiple part types while maintaining high machine utilization. System flexibility permits planning and routing adjustments in the event of demand changes and machine breakdowns. Associated advantages include higher machine productivity, shorter lead times, lower work-inprocess levels, reduced direct labour costs and consistent quality. Managing an FMS however requires more decisions than managing a traditional production line or job shop. To operate effectively, planning decisions must consider the short term interaction effects of resource utilization caused by part mix and machine tooling decisions. Real time control is required for the tool management, material handling, part routing and part dispatching systems. We are concerned in this paper with medium term planning of FMS operations. In particular, our interest centres on the process of setting up the FMS, a task performed Revision received May 1989. t Department of Systems and Industrial Engineering, University of Arizona, Tucson, Arizona 8572I, USA. This article is based upon work supported by the National Science Foundation under Grant No. DMC 85-44993.
PY - 1990/5
Y1 - 1990/5
N2 - Modern Flexible Manufacturing Systems (FMSs) are implemented to accomplish highly efficient, automated, concurrent production of several part types. The loading problem is the portion of the short to medium term FMS planning problem concerned with allocating operations and tools to machines subject to machine time and tool slot capacity restrictions. It is assumed that the set of parts along with their production goals for the period are specified. Heuristics can be readily constructed for specific objectives, but the real world problem has multiple objectives. In this paper we compare the performance of six loading heuristics on three existing FMSs. The heuristics differ in the objectives explicitly considered and in the relative priority assigned to the objectives which are considered. Performance of the heuristics is based on separate evaluation of the five objectives: workload balance, volume of inter-machine part movement, routing flexibility, tool investment and maximum machine utilization. In general, performance on the criteria is seen to differ in accord with the heuristics' objectives. However, assigning operations to machine types based on workload balance performs better than assigning to the most efficient machine type.
AB - Modern Flexible Manufacturing Systems (FMSs) are implemented to accomplish highly efficient, automated, concurrent production of several part types. The loading problem is the portion of the short to medium term FMS planning problem concerned with allocating operations and tools to machines subject to machine time and tool slot capacity restrictions. It is assumed that the set of parts along with their production goals for the period are specified. Heuristics can be readily constructed for specific objectives, but the real world problem has multiple objectives. In this paper we compare the performance of six loading heuristics on three existing FMSs. The heuristics differ in the objectives explicitly considered and in the relative priority assigned to the objectives which are considered. Performance of the heuristics is based on separate evaluation of the five objectives: workload balance, volume of inter-machine part movement, routing flexibility, tool investment and maximum machine utilization. In general, performance on the criteria is seen to differ in accord with the heuristics' objectives. However, assigning operations to machine types based on workload balance performs better than assigning to the most efficient machine type.
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U2 - 10.1080/00207549008942762
DO - 10.1080/00207549008942762
M3 - Article
AN - SCOPUS:0025429972
SN - 0020-7543
VL - 28
SP - 895
EP - 911
JO - International Journal of Production Research
JF - International Journal of Production Research
IS - 5
ER -