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MOSES: Manufacturing Organization Simulation and Evaluation SystemDepartment of Quantitative Business Analysis Louisiana State University Baton Rouge, LA 70803
IBM Corporation Shreveport, LA 71106 The key to the successful "factory of the future" will be the effective coordination of managerial functions and production operations. The simulation model described in this paper addresses this "coordination" issue, especially in terms of managing the impact of interrelated alternatives and activities in an information-rich environment. An evolutionary simulation modeling program, MOSES (Manufacturing Organization Simulation & Evaluation System), has been developed for the purpose of describing, analyzing, and understanding manufacturing organizations. MOSES is both a program and a concept. As a program, it is a menu-driven, interactive, discrete-simulation modeling tool. MOSES users are able to simulate any discrete-product manufacturing environment. As a concept, MOSES is a blend of simulation modeling and information-based management. It is structured around the idea that all manufacturing organization functions can be categorized into one of four areasmarketing, production, inventory, and accountingand that organizational success depends on decisions made by managers of those areas. MOSES users manage the organization by observing, experimenting with, and modifying the simulation-driven activities. This user interaction may take place before, during, or after the simulation process. MOSES is evolutionary in several ways: (1) the user is able to build a meaningful manufacturing organization simulation model without writing any computer code; (2) the model spans the entire manufacturing organization, not just the production function; (3) the model includes optimization techniques and heuristics along with traditional logical modeling principles; (4) the model' stores and manipulates data using database technology rather than more traditional file techniques ; (5) the system includes the user as an integral part of the simulation process.
SIMULATION, Vol. 54, No. 1,
37-45 (1990) This article has been cited by other articles:
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