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Research On Application Of Load Balance Of Surface Mount Packaging Line Based On DNA Genetic Algorithm

Posted on:2015-02-18Degree:MasterType:Thesis
Country:ChinaCandidate:H WuFull Text:PDF
GTID:2298330467467573Subject:Industrial Engineering
Abstract/Summary:PDF Full Text Request
As market’s demand and customers’ needs unceasingly to the diversifieddevelopment of personality, the product’s cycle time will be more and more shorter,Enterprises have to choose the multi-varieties and small batch manufacturing,and thecost of enterprises will gradually increase. How to respond to customers’ needs andmarket’s demands effectively and quickly, and produce qualified products in low costand high efficiency, it is the problem that enterprises must pay attention to. For SMTmanufacturing enterprises, studying load balancing of SMT production linenot onlycan improve the production efficiency, but also beneficial to make productionequipment and resources to be reasonable configuration, so it is of great significanceto the development of enterprises.This paper useDNAgenetic algorithm to construct SMT production line loadbalancing model, and expanding the application field of DNA genetic algorithm. It istrying to make different placement machines load the balance, and make the linebalance can be optimized in the premise of takt time given, it can be provide theoreticalsupport and practical help in the production efficiency of the production site and therational allocation of equipment.The main achievements of the thesis as follow:(1)Based on the research about SMT production line load balancing and DNAgenetic algorithm on the articleof domestic and foreign, it can be useful for ourtheoretical modeling, and provide an idea of using optimization of DNA geneticalgorithm to solve the SMT production lineload balancing problem. Combined with myinternship and collect data and information from practice, and find the technologyroute of research through theoretical analysis.(2)Establish the load equilibrium model of surface mounted production linebyapplication of DNA genetic algorithm and load balancing theory. Throughpracticinginthe field of SMT production line, based on the DNA genetic algorithm optimizationand improvement, constructing a load balancing model based on SMT production linein some practical constraints.(3)Empirical research on the A enterprise, to verify the feasibility of DNA geneticalgorithm and research.Numericalexperiments shows the effectiveness of the model and the algorithm, it can be used as production scheduling, for daily productionarrangementafter appropriate treatment. The study shows: DNA genetic algorithm ismore suitable for solving the load balancing problem of SMT line. First of all, becausethe total class patch element is various, if using the traditional genetic algorithmoptimization, its code length is too long, and it is not for flexible coding expression.Secondly, for this type of scheduling problem, DNA genetic algorithm can improve thelocal search ability of solution, and make premature convergence not early.(4)Proposing a series of line load balancing improvement measures. Based on theDNA genetic algorithm, solving the optimal load balancing model solution by therelevant simulation software,and study fromMan, Machine, Material and Environment,four production management elements, to proposes suggestions to improvestrategicrespectively,especially on improving the material delivery quality andimprovement in the overall efficiency of the equipment.This article is starting from the actual production field, and combined with thetheory of DNA genetic algorithm, to solve the load balancing problem in actual SMTproduction line, and it has the certain practice and innovation, can be used for SMTproduction workshop daily production activities. Can be used for SMT productionworkshop daily production activities, to improve production efficiency, makeequipment reasonable allocation, and help manage the production site.Because of mylacking of knowledge, the research in the process of DNA genetic algorithm and loadbalancing modelis not deep enough, and I will be more in-depth research on theseaspects learning in future.
Keywords/Search Tags:SMTDNA-GA, load balance, production efficiency
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