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The Application And Study On The Mid-to-short Decision Making Problems Of Balancing And Sequencing On Friction Drive Mixed-model Assembly Lines

Posted on:2013-07-20Degree:DoctorType:Dissertation
Country:ChinaCandidate:R LiuFull Text:PDF
GTID:1222330362466638Subject:Mechanical and electrical engineering
Abstract/Summary:PDF Full Text Request
The friction drive material delivery facilities developed for auto assembly have been widelyapplied in the automotive industry as the characteristic of high efficiency, flexibility and low depletionof energy. Researching on the mid-to-short decision making problems of balancing and sequencingbased on this new friction drive mixed-model assembly line is helpful for the using of theseadvantages further and will be very meaningful for the developing of Chinese auto industry.The main thinking of this dissertation is listed below: In the background of the mixed-modelassembly lines (MMAL) in which the adaptive vector-friction drive and the distributed self-controltechnologies are applied, the mid-to-short term decision-making problems have been discussed.Connection between the balancing and sequencing of the MMAL integrated with the characteristicsbrought by the new conveyor has been explored and the combined affect on the MMAL has been paidclose attention to. The whole research has been analyzed from different points of view: First, theimpact of various factors on production efficiency for different kinds of MMAL brought by newtechnologies has been studied. Mathematical models of the balancing and sequencing (B&S)problem with appropriate objective functions have been proposed; Second, correspondingevolutionary algorithms for different optimization models have been designed. The structures of thealgorithms have been designed and some key operators have been improved in order to enhance theperformance of these algorithms. Considerable contrastive experiments have been carried out and theresult data shows the improvement brought by some innovative operators and the superiority of thealgorithm. In order to certify the effectiveness of the algorithms further more, some results of thealgorithms have been modeled. During the process of simulating, appropriate control properties andmethods have been set up in the simulation models of eM-Plant software. At last, for the applicationof the theory, the optimization software of balancing and sequencing which integrates all the theoriesand algorithms of this dissertation has been developed. Then the preliminary application increases thepracticality of this research. The main subjects are as follows:First, the friction drive assembly line has a low cycle time and many different kinds of models.These characteristics have become new challenges in balancing and sequencing problems. Clonalselection algorithm, the basic algorithm of this research, has been first introduced. Then a novelvaccine co-evolutionary clonal selection algorithm has been proposed. The coding and evaluationoperators of vaccine populations have been designed. This new algorithm has been applied for bothsingle-objective balancing problem and multi-objective sequencing problem. Meanwhile, a newcoding strategy has been devised for the balancing problem and a new evaluation method has beenraised to make up for the deficiency that different coding often has the same fitness in the sequencingproblem.Second, the flexible-swayed friction drive and the displacement self-compensate friction driveare core technologies of friction drive technologies. These provide the assembly lines with highflexibility and convenience for the layout of compact U-shaped lines and space-crossed lines. Theimpact on the work-time of workstations caused by the mixed-model production mode has beendisplayed, which highlights the necessity of optimization from both balancing and sequencing. Multiple objections of balancing workload, minimizing the part usage variation and minimizing thesetup cost have been optimized by an immune co-evolutionary algorithm which is designedconsidering both the connection and distinguish between the balancing and sequencing problem. Avirtual union-model method is developed for the short of basic controls so that the simulation byeM-Plant can be executed on U-shaped assembly lines.Third, minimizing the utility work time has been adopted as the objective function of the B&Sproblem of straight shaped assembly line. The mathematical model of optimizing workload from bothbalancing and sequencing has been established. A novel hybrid strategy based on immune clonalselection algorithm and local search algorithm has been brought up for this complex problem.According to the characteristic of the assembly line come up with the distributed self-controltechnology, variable cycle time has been adopted to further reduce the unbalance of the workstations.Considering the relationship between those variables, a hybrid co-evolutionary algorithm whichcombines both synchronous evolution and asynchronous evolution has been raised so that theperformance and efficiency of the algorithm can be improved. A simulation method using “Line”control and “method” control has been designed and applied in order to simulate the objectivefunction exactly.Fourth, considering the lack of related researches for rebalancing problem, the rebalancing andsequencing problem caused by changing orders has been given. The strategy of adjusting sequencesusing single pull-off table between different lines has been proposed. Proper coding and decodingoperators of multiple–objective clonal selection algorithm have been designed for this resequencingproblem.Based on the theory of this dissertation, the software of balancing and sequencing system hasbeen developed. This system has been divided to six functional modules: the production datamanagement module, the algorithm configuration module, the balancing module, the balancing andsequencing module, the sequencing module and the rebalancing module. This system can providetechnical support for the optimization of production considering different objectives of differentphases. The operating effects of this system has been elaborated and compared in detail in order toprove the correctness of the theory and the effectiveness of the system of this research.At the end of this dissertation, the summary of the innovations in this research has been givenand the further research has been forecasted.
Keywords/Search Tags:Mixed-model assembly lines, mid-to-short term decision making, balancing andsequencing, vector-friction drive, distributed self-control, clonal selection algorithm, co-evolutionary algorithm, eM-Plant
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