Improved Genetic Algorithms And Its Application In Process Planning Optimization

Optimization of process planning is the important method to ensure product quality, to improve efficiency and to reduce cost.This dissertation discussed the research status in quo of Computer Aided Process Planning system and Process Optimization. A layered strategy to process planning was presented: First, assembled the processing methods chain of machining features; Second, sorted the process units in order to satisfy Optimization objectives and common sequencing constrains; Then, the whole process route was acquired by inserting assistant processes.On the base of the advantages and shortcomings of Genetic Algorithms, Tournament selection with parent-offspring competition and Simulated Annealing in crossover and variation were put forward. The improvement was verified by some typical test functions.A combinatorial optimization model for process scheme is presented .The optimization goal includes best machining qualities, least machine kind and shortest process route. Based on the analysis of typical process plans for prismatic box, an approach used of group technology to determine the priority of the machining unit was put forward. The mathematical model to transform costs of machines, fixtures, tools and other ancillary costs for process sequencing optimization is constructed. Holes Machining Path Planning is significant to improve the machining efficiency and quality of multi-hole parts. A mathematical model to minimum production cost was setup.The corresponding encode mode and genetic operations for the above model were designed. The optimal solution on the use of improved genetic algorithms was identified and three instances were validated.The soft modules for process sequencing optimization were designed and achieved. In the end, the structure and interface of Process Optimization prototype system was introduced.