装配成功率可控、面向成本优化的尺寸链容差设计

Research on A Tolerance Design Method of Dimensional Chain for Controllable Assembly and Cost Reduction

采用蒙特卡罗法求解、遗传算法优化来进行尺寸链容差设计,设计目标是在装配成功率真实可控的前提条件下尽量优化机械加工的成本。通过深入分析,装配成功率经成本优化后会极限接近合格线,这样会导致两个问题:(1)经重复多次采样,装配成功率的值分布在及格线上下,其中大量不合格;(2)遗传算法每代最优个体无法长久保存,导致优化效率低下。文中采用二次采样蒙特卡罗法将装配成功率的采样波动纳入考虑,有效解决了上述两个问题,得到的结果更符合设计目标的要求。

This article presents a tolerance design method for dimensional chains based on the Monte Carlo method and the genetic algorithm to achieve controllable assembly and cost reduction.It is found that the assembly success rate will approach the qualified limit to the extreme after cost reduction,which can lead to two problems:(1)after repeated sampling,the value distribution of the assembly success rate is around the qualified limit,with a large number of unqualified values;(2)the optimal individual of each generation in the genetic algorithm cannot be saved for a long time,resulting in low optimization efficiency.This article adopts the second sampling Monte Carlo method to take into account the sampling fluctuation of assembly success rate,effectively solving the above two problems.