A simulation approach for cellular manufacturing system design and analysis
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Often, real world decisions require some degree of human judgment. These decisions may require a set of tools that can assist the decision maker. Simulation modeling, MRP, MRPII, decision trees, and linear programming are some examples of the types of tools used for Decision Support Systems. This chapter presents the application of linear programming to develop a methodology that uses design and manufacturing attributes to form machining cells. The methodology is implemented in four phases. In Phase I, parts are coded based on the proposed coding system. In Phase II, parts are grouped into families based on their design and manufacturing dissimilarities. In Phase III, the optimum number of resources (e.g., machines, tools, and fixtures) are determined and grouped into manufacturing cells based on relevant operational costs and the various cells are assigned part families. Finally, in Phase IV, a simulation model of the proposed system is built and analyzed. This model is executed so that data from the proposed system may be gathered and evaluated to justify the feasibility of the system by introducing real-world scenarios such as breakdown, maintenance, and on-off shifts. The developed mathematical and simulation models are used to solve a sample production problem. The results from these models are compared, and are used to justify the final design of the cell. By using these modeling techniques and tools, cellular manufacturing systems can be designed, analyzed, and finally optimized. © 1995 Elsevier B.V.
author list (cited authors)
Kamrani, A. K., Parsaei, H. R., & Leep, H. R.