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• W1992657905 abstract "Abstract In this paper, we consider the FMS planning problem of determining optimal machine workload assignments in order to rninimize mean part flow time. We decompose this problem into the subproblems of first forming machine groups and next assigning operations to these groups. Three types of grouping configurations—no grouping, partial grouping and total grouping—are considered. In both no grouping and partial grouping, each machine is tooled differently. While each operation is assigned to only one machine in no grouping, partial grouping permits multiple operation assignments. On the other hand, total grouping partitions the machines into groups of identically-tooled machines; each machine within a group is capable of performing the same set of operations. Within this grouping framework, we consider three machine loading objectives—minimizing the total deviation from the optimal group utilization levels, minimizing part travel and maximizing routing flexibility, for generating a variety of system configurations. A queueing network model of an FMS is used to determine the optimal configurations and machine workload assignments for the no grouping and total grouping cases. It is shown that under total grouping, the configuration of M machines into G groups that minimizes flow time is one in which the sizes of the machine groups are maximally unbalanced and the workload per machine in the larger groups is higher. This extends previous results on the optimality of unbalancing both machine group sizes and machine workload to the mean flow time criterion. A simulation experiment is next conducted to evaluate the alternative machine configurations to understand how their relative performance depends upon the underlying system characteristics, such as system utilization level and variation among operation processing times. We also investigate the robustness of these configurations against disruptions, such as machine unreliability and variation in processing batch sizes. While different configurations minimize mean flow time under different parameter values, partial grouping with state-dependent part routing performs well across a wide range of these values. Experimental results also show that the impact of disruptions can be reduced by several means, such as aggregating operations of a part to be performed at the same machine, in addition to providing routing flexibility." @default.
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• W1992657905 title "PRODUCTION PLANNING DECISIONS IN FLEXIBLE MANUFACTURING SYSTEMS WITH RANDOM MATERIAL FLOWS" @default.
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• W1992657905 doi "https://doi.org/10.1080/07408179408966624" @default.
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