Genetic Algorithm Is Applied To Optimization Design Of Runner System Of Injection Mould

In many cavity injection mold designs, the runner system is used to send matter and keepspress. The runner system is reasonable or not, which influences goods apparent quality, placedimension, physics dynamics capability, difficulty of filling mold and flow estate of meltmaterial in filling mold time. Runner system includes gate, sprue and runner. Gate is moreimportant in runner system, number and place of gate mostly affect filling manner. Moreover,shape and dimension of gate confirm way and balance of polymer flow.Conventional flow balance is based on deviser's experience, time after time try andadjusting path, as well as gate dimension. It takes time and hard sledding. CAE technology candope out runner capability before making mold, which can improve ratio of first testing mouldsuccess. In order to fill balance, we may combine CAE technology with optimization, use resultof CAE simulation and recur to optimization theory to construct effective arithmetic to optimizethe runner system. To implement automatic optimization of the runner system of injection mouldis necessary trend of development of injection mold CAE technology.The optimization of injection runner system, which is based on Numerical Simulation offilling process, is implemented by using Genetic Algorithm (GA). We may easily get somedatum, such as the different distributing of pressure and the filling time of cell of each cavity, invirtue of Numerical Simulation of filling process. The datum provides the direct gist to use GA.In virtue of computer program, the result of resolved question is expressed as chromosome inorder to construct population, and they are placed in circumstance of the problem. Afterwards,according to principle of the fittest, chromosomes which are seasoned with circumstance arechose to reproduce. And only by crossover and mutation, it may produce new populations whichare more adaptive to the circumstance. By many times alteration, it converges to a most adaptivepopulation. Namely, we get optimization result.In my paper, I will adopt Genetic Algorithm and numerical simulation to optimize injectionrunningsystem. By optimizing injection running system, I can confirm size of injection runnersystem to reach a optimal filling balance. Its main work is as follows: 1. I will construct Mathematical model (objective function and constraint) and predigestappropriately the model on the basis of thorough analytic of filling process of model andconsideration of pressure of model cavity and time of injection.2. On the basis of numerical simulation of filling process, we adopt GA to solve theproblem. In the process of calculation, it confirms genes expression of injection runner system,function of adapting degree and standard of it by transforming appropriately the aim function.And it adopt coding mode of binary system to carry out a serial of operation, such asreproduction, chiasm, aberrance, for chromosome. At the same time, it adjusts arithmeticoperators of chiasm and aberrance by way of avoiding occur of earliness phenomenon.3. I will write the program of optimizing system and validate it. Provided the size of aroundoptimization of injection runner system, it gets distributing status of pressure after optimization,which shows rationality and correctness of program of optimal design.