Dynamic models for the analysis of manufacturing systems

被引:0
|
作者
Crain, CR [1 ]
机构
[1] Miami Univ, Richard T Farmer Sch Business Adm, Dept Management, Oxford, OH 45046 USA
来源
关键词
discrete simulation; model design; manufacturing;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
A critical examination of manufacturing systems usually begins with the definition of a structure around which these systems can classified and from which common principles can be defined. One such classification framework is based on the dominant resource/product interactions that are present in the manufacturing process. This framework allows nearly all manufacturing systems to be classified into one of three (3) major categories designated as V, A, or T configurations. The classic V configuration is dominated by a system characterized by a single product being transformed by relatively standard processes into several distinct end items. The classic A configuration is dominated by multiple resource/product interactions generally converging, usually with assembly operations, into one or two end items each with a unique set of component parts. The classic T configuration is dominated by product/resource interactions where a subset of common component parts is assembled at the final assembly stage to create multiple end items. The principal objective of this paper is to describe three (3) discrete event simulation models, one for each of these fundamental configurations, that were developed as "laboratory models" for a course in operations planning and scheduling. A subordinate objective of this paper is to offer a critical evaluation of the effectiveness of these models as supplements to the traditional lecture, case analysis, and class discussion method of instruction. The models were developed for a senior-level and MBA-level class in operations planning and scheduling at an AACSB accredited School of Business. The software platform, X-CELL+ Factory Modeling System, Release 4.0 was developed by several members of the faculty at the Johnson Graduate School of Management and the School of Operations Research and Industrial Engineering at Cornell University and is distributed through The Scientific Press, San Francisco, CA. A copy of the computer code for each of the models is also available from the author.
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页码:163 / 167
页数:5
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