Abstract
In this paper, a new formulation model for cellular manufacturing system (CMS) design problem is proposed. The proposed model of this paper considers assembly operations and product structure so that it includes the scheduling problem with the formation of manufacturing cells, simultaneously. Since the proposed model is nonlinear, a linearization method is applied to gain optimal solution when the model is solved using direct implementation of mixed integer programming. A new genetic algorithm (GA) is also proposed to solve the resulted model for large-scale problems. We examine the performance of the proposed method using the direct implementation and the proposed GA method. The results indicate that the proposed GA approach could provide efficient assembly and product structure for real-world size problems.
Highlights
Cellular manufacturing system (CMS) is one of the most important tools on improving the flexibility of any production planning (McAuley, 1972)
We have presented a new mathematical model for CMS design problem included cell formation and scheduling simultaneously where the assembly operations and product structure are taken into consideration
The proposed model was formulated as nonlinear mixed integer programming and has been simplified using some auxiliary binary variables
Summary
Cellular manufacturing system (CMS) is one of the most important tools on improving the flexibility of any production planning (McAuley, 1972). Cell conversions primarily focused on the conversion from a functional to a cellular layout He used simulation model using some real-world data to measure the impact of each factor on the estimated performance improvement resulted by converting assembly lines to assembly cells. Panchalavarapu and Chankong (2005) studied assembly aspects in the context of cell formation problem (CFP) and proposed a new idea of assembling the parts in the same cells where the production of the parts happen They proposed a mathematical model which uses a new similarity coefficient among part, machine and subassembly to determine the suitable assignments to manufacturing cells.
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