Balancing Research Of Mixed-flow Assembly Line Based On Improved Genetic Algorithm

As society and the economy continue to prosper,the rich personalized needs of consumers bring opportunities and challenges to manufacturers,and the mixed-flow assembly line is widely used as an efficient production method.The advantage of mixed-flow assembly lines is the ability to simultaneously assemble a variety of customized,individualized products with similar structures,providing customers with competitive products at low cost and short delivery times,and widely used in modern manufacturing production.Customer orders change frequently,resulting in changes in the type,quantity,and delivery time of the company's products,requiring the existing assembly line to be rebalanced and redesigned in a time-consuming manner.Compared to single product assembly lines,the complexity of mixed assembly increases due to the different processes,processing times,loading intervals,and component sizes for multiple products.Therefore,how to optimize the balance of the mixed-flow assembly line to achieve higher productivity,shorter cycle time and lower equipment idle rate is an urgent problem for modern manufacturing companies.Firstly,this paper summarizes and analyzes a large amount of domestic and foreign literature on the basis of research ideas,and elaborates on the balance problem of mixed-flow assembly line,industrial engineering methods and intelligent optimization algorithms,and uses them as the theoretical basis to analyze the automotive center control mixed-flow assembly line of Suzhou Ampofo Electronics Co.The traditional industrial engineering method is used to improve the overall operation and operation content of the line initially,and a mathematical model with the objectives of minimizing the production beat,load balancing between stations and minimizing the loss time within stations as the line balance optimization is established.Secondly,this paper proposes an improved genetic algorithm using simulated annealing algorithm to improve the genetic algorithm,and the effectiveness of the improved genetic algorithm is derived through algorithmic verification.The program is written and debugged on Matlab software to optimize the simulation of the improved equilibrium problem of the automotive central control mixed flow assembly line of Suzhou Ampofo Electronics Co.Finally,Flexsim simulation software was used to build simulation models before the improvement of the assembly line,after the initial improvement of industrial engineering and after the further optimization of the improved genetic algorithm and to compare and analyze the results,which proved the practicality of the improved genetic algorithm proposed in this paper to solve the mixed-flow assembly line balancing problem.