Multi-Objective Optimization Manufacturing Cell Layout Research Based On Genetic Algorithm

With the increasing global competition with in the field of manufacturing, more and more manufacturers and researchers are aware of the importance of the facility layout in the manufacturing system, which is a long-standing and important task in industrial and engineering field .A good facility layout planning will improve manufacturers ’production efficiency and quality. At the same time, Cellular Manufacturing (CM) is regarded as an advanced flexible manufacturing mode in resent years, whose performance is dependent on facility layout design especially. The layout problem in cellular manufacturing system using group technology is investigated in this thesis.The background and the orientation of our research is put forward in this article. Then a summary of the achievement carried out by predecessors in the field of equipment layout is presented, and kinds of equipment layout models and solution algorithms are explained and compared. Because layout design is a complex combinational optimal problem, and in view of the NP-hard characteristics of layout problem, Genetic Algorithm is chosen to solve this problem.Anatomizes each element in the plant equipment layout problem, and according to the production process route, author reduce the production shop to five basic forms, and divide the equipment linear layout in cell into four forms. At the same time, U-shaped is taken as the layout form in this article. Whereafter, according to the characteristics of equipment layout in Production workshop, four main goals are proposed. Then author gives the objective function of the layout model, as well as its detailed computational method.The layout of the fixative Manufacturing Cell is carried out, and the final equipment layout formed. Supposing that processing plant of every component is known and invariable, so a mathematical model of layout in cellular manufacturing system is explored and presented, and the material handle cost between cells, the utilization ratio of plant area are taken as the optimization target in this model. In the end the solution was given by the genetic algorithm.Finally, an accompanying equipment layout study about BRWH Co. is given as an example to show the feasibility of the design given in this article, after comparing the real result with the ideal result. At last, the thesis summed up the shortages of the design given in this article and gave suggestions about the solution as well. p.s. the programs are completed on the base of MATLAB and Visual C++.