Optimization of process based on adaptive ant colony algorithm

To solve the optimal process planning problem in the computer aided process planning, an optimal process planning method based on adaptive ant colony algorithm (AACA) and taken minimal replacement rate of manufacturing resources as optimization objective is proposed. The manufacturing feature is sub-divided into manufacturing procedures according accuracy requirement, and then the concept of machining cell which is composed of manufacturing feature, manufacturing procedure, manufacturing method, manufacturing resource and fixing location is introduced. Therefore the process planning could be represented by an optimal arrangement to the machining cells. A matrix of constraints to Machining cells is constructed according the constraints of geometrical location among manufacturing features and the priority among manufacturing procedures. The least replacement rate of manufacturing resources, which represent unified seeking for less time-to-market, higher quality and lower cost, is taken as the optimization objective. Under the constraints of the matrix of constraints to machining cells and the available manufacturing resources, the AACA is adopted to solve the model. An example is given to demonstrate that our method is reliable and effective to produce the process plan in accordance with the real practice.