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Balance Method Research Of Mixed-model Assembly Lines In Multi-product Small Batch Discrete Manufacturing Enterprises

Posted on:2016-01-17Degree:MasterType:Thesis
Country:ChinaCandidate:Y F LiuFull Text:PDF
GTID:2308330479499248Subject:Management Science and Engineering
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Mixed-model assembly line, as a kind of high efficient flexible mode of production, has been widely used in the discrete manufacturing enterprises. However, when the assembly line put into operation after a period of time, due to the change of product demand ratio, the investment of new products and the change of the assembly time of operation, generally there are some problems such as: uneven busy time for each station, frequent congestion and waiting problem, which decrease the production efficiency obviously. To make mixed-model assembly line produce high efficiently, more flexibility and reliability, we must continuously improve the adaptability of mixed-model assembly line for the market, and give the new equilibrium solution of the mixed-model assembly line in time in the operational phase.Through the literature research, we can find that the mixed-model assembly line balancing problems are generally divided into I and II balance issue. The mixed-model assembly line balancing problems I(MMALBP-I for short) refers to the known production beats, minimization the number of workstations, which is often taken into consideration in the a assembly line design and installation of stage. The mixed-model assembly line balancing problems II(MMALBP-II for short) refers to the known number of workstations to minimize the production beats, which is often taken into account a assembly line operation stages. At present, most of researches have focused on MMALBP-I. In the few studies of MMALBP- II, beat optimization process is complicated, or the optimization goal is single. The solving method which usually using genetic algorithm(GA) often exist limited search space problem, the shortcoming of easily plunged into local optimum. Therefore, it is necessary to further explore the methods of solving MMALBP – II in order to get a better balance effect.First of all, according to the balance status and the actual need about balance of mixed-model assembly lines in many multi-product and small batch discrete manufacturing enterprises, the thesis systematically analyzes the mixed-model assembly line balancing problem. Secondly, combined with characteristics of the mixed-model assembly line in discrete manufacturing enterprises, the paper build up a mathematical model of MMALBP – II, which is designed to minimize the production rhythm, balance the load among stations. When it comes to the methods to solve the problem, the improved genetic algorithm is used, whose biggest characteristic is two populations with different ways of crossover and mutation. Each evolutionary generation exchange the optimal individual of the two populations and random individuals to break the equilibrium within the population to a higher equilibrium and to jump out of local optimum. Additionally, according to the characteristics of the MMALBP- II, the suitable ways of encoding and decoding, transformation of fitness function are designed, which use MATLAB software to implementing the algorithm. Afterwards, the example of comparison and analysis, as well as the study of the mixed-model assembly line balancing in company S standard gear speed reducer assembly, prove the feasibility and effectiveness of the algorithm. Using the balance method designed in this paper can achieve very good effect on mixed-model assembly line balancing. Especially when the external market environment is always under constantly changing, it is necessary to adjust the assignment allocation solutions of the mixed-model assembly line in time, so as to response to market needs to largest extent. Owing to the characteristics of less time-consuming, convenience, feasibility of the balance method, it can be widely used to provide useful references for the same type of enterprises.
Keywords/Search Tags:mixed-model assembly line, class II balance issue, the double-population genetic algorithm
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