Balancing Problem Reseach Of Mixed Model Assembly Lines Based On Petri Nets

Assembly line is a typical flow guidance system in the production system, which isthe important component of the modern industrial mass production. As the diversity ofcustomer demand and personalized need, the mixed flow assembly line arises at thehistory moment. Mixed flow assembly line balancing is an important part of theproduction planning and assembly line management. It can achieve the overall balance ofassembly line production efficiency and equipment utilization. Therefore, the method ofselection has a crucial impact on the balancing effect.This paper adopts object-oriented Petri net modeling, and the improved geneticalgorithm to solve the balancing problem. The main research works of the paper areoutlined as follows:First, the research status at home and abroad of the modeling and balancing problemfor the mixed flow assembly line system is described and analyzed. According to theadvantages and disadvantages of each method, this paper gives the importance andpractical significance of the mixed flow assembly line balancing problem.Second, an object-oriented and Petri nets are used in the auto parts seat line modelingstudy. This paper has carried on the modeling and analysis from three aspects which arethe assembly unit module, the resource module and the overall module. Each module indetail elaborates the internal structure and operation mode. In addition, it also illustratesthe relationship with other modules and message invocation mechanism. Finally, itvalidates the effectiveness of the method through the model analysis.Finally, after establishing system model, the improved genetic algorithm is proposedto solve balancing problem for minimizing the number of workstations and smooth indexas the target in the paper. According to the characteristics of the problem, the codingscheme bases on feasible sequences encoding. Initialization combines the heuristicstrategy and random strategy to ensure the effectiveness of the solution space. Combiningthe optimal preservation strategy and roulette wheel selection method, the selectionmethod not only ensures individual diversity, but also not lose good individual. Finally it validates the feasibility and effectiveness of the algorithm through an application example.