Research On The Optimization Of Assembly Line Balance For D Product Of Q Company

With the development of economic globalization,the number of products in demand is constantly rising,and the competition among manufacturing companies is becoming more and more intense.Only by continuously improving the manufacturing level can we ensure the sustainable development of manufacturing enterprises.As one of the common production lines of manufacturing enterprises,the optimization of the assembly line balance problem can effectively improve the efficiency of enterprises.In this paper,we take the D product assembly line of motorcycle manufacturing company Q as the research object to study its assembly line balance problem.In the research process,firstly,we analyzed the current situation of the company’s assembly line through field visits,job measurement and Flexsim simulation tools,and identified three key factors affecting the balance of the line: uneven distribution of work stations,bottleneck process constraints,and unreasonable work sequences;secondly,we used the "5W1H" questioning technique and the "ECRS" principle to improve the problem of unreasonable work station distribution.Secondly,the "5W1H" questioning technique and the "ECRS" principle were applied to improve the problem of unreasonable workstation allocation;the bottleneck process of the assembly line was optimized by using process procedure analysis,two-hand work analysis and workstation improvement.In addition,the mathematical model was established with the second type of line balancing as the target,and the simulated annealing particle swarm algorithm was introduced to solve the process allocation scheme when the number of workstations is 17 using the particle swarm algorithm,simulated annealing algorithm,and simulated annealing particle swarm algorithm,and the effectiveness of the algorithm was verified;at the same time,the simulated annealing particle swarm algorithm was used to solve the process allocation scheme when the number of workstations is 16,15,14,and 13,and the line balancing rate and the number of production per shift were used as indicators.At the same time,the simulated annealing particle swarm algorithm was used to solve the process allocation schemes for 16,15,14 and 13 workstations,and the line balance rate and the production quantity per shift were used as indicators for comparison and analysis.Finally,the line balance rate,smoothing index,and labor cost per unit of product before and after optimization are compared and analyzed.Through this assembly line balance optimization study,the balance rate of D product assembly line was improved,the cost per unit product of the enterprise was reduced,and the economic benefits of Q company were effectively increased,which provided reference significance for other enterprises’ assembly line balance optimization study.