Selection of Distributed Manufacturing Environments Based on Genetic Algorithm for Automobile Gears

Abstract

Aiming at the optimization problem of distributed manufacturing environments, a mathematic model based on genetic algorithm (GA) was established. When establishing the mathematic model, the minimizing production cost and the minimizing production time were selected as the optimization objects; at the same time, the two-dimensional symbol string encoded by integer encoding was used to represent chromosome. To optimize the distributed manufacturing environments, the factors influencing production cost can be classified as four indices: machine change cost, tool and grinding wheel change cost, set-up change cost, and machining cost. The factors influencing production time can be classified as four indices: machine change time, tool and grinding wheel change time, set-up change time, and machining time. The processing of four-grade intermediate shaft gear of an automobile transmission was used as an example to prove the validity of the proposed model, and the analysis results of examples show that the optimization model can select the optimal manufacturing environment based on the different demands effectively and objectively.