Research on optimization of assembly line based on product scheduling and just-in-time feeding of parts

Purpose Reducing production auxiliary time is the key to improve the efficiency of the existing mixed-flow assembly line. This paper proposes a method combining improved genetic algorithm (GA) and Flexsim software. It also investigates mixed-flow assembly line scheduling and just-in-time (JIT) parts feeding scheme to reduce waste in production while taking the existing hill-drop mixed-flow assembly line as an example to verify the effectiveness of the method. Design/methodology/approach In this research, a method is presented to optimize the efficiency of the present assembly line. The multi-objective mathematical model is established based on the objective function of the minimum production cycle and part consumption balance, and the solution model is developed using multi-objective GA to obtain the mixed flow scheduling scheme of the hill-drop planter. Furthermore, modeling and simulation with Flexsim software are investigated along with the contents of line inventory, parts transportation means, daily feeding times and time points. Findings Theoretical analysis and simulation experiments are carried out in this paper while taking an example of a hill-drop planter mixed-flow assembly line. The results indicate that the method can effectively reduce the idle and overload of the assembly line, use the transportation resources rationally and decrease the accumulation of the line inventory. Originality/value The method of combining improved GA and Flexsim software was used here for the first time intuitively and efficiently to study the balance of existing production lines and JIT feeding of parts. Investigating the production scheduling scheme provides a reference for the enterprise production line accompanied by the quantity allocation of transportation tools, the inventory consumption of the spare parts along the line and the utilization rate of each station to reduce the auxiliary time and apply practically.

Automated summary

This paper proposed a method combining improved genetic algorithm (GA) and Flexsim software to reduce production auxiliary time and improve the efficiency of existing mixed-flow assembly line. By establishing a multi-objective mathematical model and developing a solution model using multi-objective GA, the method effectively reduced idle and overload of the assembly line while rationalizing transportation resources and decreasing line inventory accumulation. The originality lies in the first intuitive and efficient use of the combination of improved GA and Flexsim software to study production line balance and just-in-time feeding of parts.