Research On Automobile Parts Disassembly Sequence Planning Based On Disassembly Network Graph

With the booming development of the automotive industry, the yield and the amount of automobiles are rising rapidly. At the same time, the number of old automobile is increasing. The recycling of the automobile is helpful to solve the problem of resource shortage and environment pollution. Disassembly sequence planning is one of the most important parts of product disassembly recycling research. The quality of disassembly sequence would affect the cost and efficiency of disassembly. It also affectes the quality of components and cost of product maintenance. Based on the inland and outland researches on this field, this paper studied the model and the optimization algorithms of disassembly sequence planning. Then this paper proposed a method of disassembly sequence planning.This paper analyzed the disassembly information and proposed a series of principles to establish network graph of automobile disassembly. The network graph of automobile disassembly could indicate all the automobile disassembly sequence. The transition matrix is used to express constrained relationship among the components. The adjacent matrix is used to express the weight of disassembly, such as the cost time and benefit of disassembly. Thus the model of automotive disassembly is established in the paper.Then, suitable target functions are constituted. This paper mapped the Floyd algorithm to disassembly model by combining the characteristics of disassembly sequence planning. Then it utilized the algorithm, which is used for solving shortest route problem, to solve the model of automotive disassembly and obtained the optimization disassembly sequence. Thus the automobile disassembly sequence planning is combined with the Floyd algorithm.At last, in order to illustrate the validity of the model and the Floyd algorithm. This paper studied the silicon oil clutch assembly and obtained the disassembly sequence with three different objectives. The results show that the model is validity and the algorithm is feasibility.