Research On Dynamic Balance Problem Of Mixed-flow Assembly Line Based On Improved Particle Swarm Optimization Algorithm

With the market competition and the diversification of customer needs increasing,job shop manufacturing has been one of the main production mode in industrial enterprises.A variety of products with similar production structure and similar process can be assembled and manufactured on the same assembly line,and no need to increase the inventory of the manufactured products.The mixed model assembly line has been widely used in manufacturing enterprises because of its high flexibility and strong response to the market.At present,most studies focus on the initial balance problem of the mixed model assembly line.In the actual production,however,the initial assembly line balance is affected by many dynamic factors caused the loss of balance,such as changes in production schedule affect the proportion of product changes,product upgrades to improve the assembly process to increase,replace or delete,assembly technology progress resulting in changes in operating time,and so on.These situations caused by the dynamic balance problem of mixed model assembly line.Therefore,it is of great theoretical and practical significance to study the dynamic balance of the mixed model assembly line.The research contents of this thesis are as follows:1.Dynamic factor analysis for mixed model assembly line balancingThis paper shows the influence of the change of market demand,the change of product characteristics and the progress of assembly technology on the production of mixed model assembly line.The assembly tasks on the assembly line should be re allocated reasonably.In order to make full use of the existing equipment and human resources on the assembly line,it divides the difficulty of assembly tasks and the skills of operators,and establishes the matching relationship between them,and draws up the standard for calculating the cost of re-balancing.2.Establishing a mathematical model of mixed model assembly line balancingThe realization of dynamic balancing of mixed model assembly line requires reasonable redistribution of the assembly task.Assigning suitable difficult assembly tasks to a reasonably skilled operator can make better use of existing equipment and human resources in the enterprise.In this paper,two main categories are considered to realize the re balancing adjustment cost.One is the adaptation cost,which refers to the assignment of new tasks to the operator that he is now capable of completing,and the operator will need the cost for an adaptation period.The other is the learning cost,which refers to the operator was assigned the assembly task he is currently unable to complete,and the operator need the cost to learn the corresponding operation skills to complete the task.The establishment of dynamic balance model of mixed model assembly line is necessary to ensure that the task of assembly is assigned to workstations reasonably and evenly,and the minimum adjustment cost of the re-balancing.Finally,the mathematical model of dynamic balance of mixed model assembly line is established,which takes the cycle time,the load fluctuation of the workstation and the adjustment cost as the optimization objective.3.Improved particle swarm optimization algorithmThe improved particle swarm algorithm(PSO)is used to solve the optimal solution ofthe dynamic balance problem of the assembly line.Based on the standard particle swarm algorithm is easy to fall into local extremum,this paper designed a new improved particle swarm algorithm,and the algorithm from the increased diversity of particle population and search capability perspective to improve the standard particle swarm algorithm.The improved algorithm program is written in MATLAB language,and the optimal solution of the model is obtained.4.Examples are given to validate the model and algorithmThe engine assembly line of a loader was taken as an example to verify the accuracy of the model and the effectiveness of the improved algorithm.In this paper,the application of dynamic balance of mixed model assembly line is studied.The mathematical model was established by analyzing the relevant data.The improved particle swarm algorithm was used to obtain the optimal solution of the model.At last,the correctness of the model and the effectiveness of the algorithm were verified by the example results.