The Research Of Assembly Sequence Planning Based On Genetic Algorithm

Assembly is the end of manufacture process, assembly quality affect product's performance in high degree, and assembly cost is a big part of the manufacture cost. With the manufacture mode transfer from single and volume produce to varieties, little batch and high quality, assembly takes a more and more proportion in manufacture. So pre-assembly and analyzing in design and assembly programming is more important for improving product's quality and reducing production cost. Based on the introduction of the project background and interrelated research, the evaluation and optimization of assembly planning are researched. An approach of assembly sequence's evaluation and optimization based on genetic algorithm is proposed, on the background of based-on-feature assembly model and analysis of assembly, the generation and evaluation and selection of assembly sequence is realized.In this paper, a situation of assembly model is introduced, and concentrated in the analysis of arrangement-model, and make planning to assembly sequence at the base of this model.The evaluation and optimization of assembly sequence is difficulty and important in ASP system, which related to many factors. Assembly sequence will be evaluated correctly and objectivity after the information-gained and qualitative analysis and quantitative analysis of the factors. In this paper, set-pair analysis (SPA) theory is used in evaluating the assembly sequence with an object of the perfect cost. The interrelated definitions of set-pair analysis is introduced, and give an evaluation approach based on affiliation degree and set-pair state, the optimal sequence is confirmed through review the degree of concurrent and the times of reorientation and the maximum number of parts be assembled in one orientation. The ASP is a combinatorial evaluation process; the genetic algorithm is used in this process because of its characteristic. Chromosome coding and fitness function constructing are two main issues. In the end, several examples are given to improve the validity of this evaluation approach by a programme, which is programmed by MATLAB.