Research On Multiple Objective Sequencing Problems In Mixed Model Assembly Line With Consideration Of Line Balancing

As a mode of production with general application under the current context of mass customization, mixed-model assembly is used to assemble product family which sets similar in function and structure with each other. The assembly lines can effectively meet the needs of multi-variety and small-batch production. To maximize the efficiency of the assembly line, the reasonable order the production plan must be considered. Within this rapidly changing environment, the mixed-model lines scheduling problem becomes a short-term production problem and developing methods to solve this problem both efficiently and quickly gains importance more than ever. By taking a high-voltage switchgear company as the research object, use Plant Simulation to model, simulate and optimize the mixed assembly lines, and the method was proved to be more effective compared with Goal Chasing.Firstly, on the basis of theoretical research on discrete event system simulation, the paper summarizes the specific implementation steps for the production system modeling, simulation and describes the features and development of Object-Oriented Simulation, and takes software Plant Simulation as a tool to do a detailed explanation. Then a mathematical model was provided considered three important objectives, such as minimizing change rate of part usage, total utility work and total setup time of mixed-model assembly lines for product families, and uses the Weighted Method to transform multi-objective problem into a single-objective problem.Through the detailed analysis of the actual production situation of the assembly line of a high-voltage switchgear company, then establishes a simulation model of production system by reducing some parameters. Under the premise of the assembly lines balancing, and genetic algorithm was applied to get the satisfied production sequence considering the goal of minimizing process time. in the view of assembly line balancing, the simulation analysis was carried out based on the group of satisfactory solutions proposed by the genetic algorithm, and the optimal solution was defined. The algorithms is compared with Goal Chasing which has developed a wide range, the comparison shows the results obtained by using the system simulation optimization is more satisfying.