Optimal Tolerancing: The Link Between Design and Manufacturing Productivity

将开发一种计算设计工具，以便对机械和电气部件进行最佳公差分配。基本方法是将非传统优化方法与基于蒙特卡罗的公差分析程序相结合。以最佳方式分配公差的能力将允许以最高效的方式利用已安装的资本基础。该技术的成功应用将对降低制造成本和产品周期时间以及提高生产率、质量和客户满意度产生巨大影响。目前工业中使用的公差分析不能提供以最佳方式分配公差的能力。传统的非线性规划方法不能很好地解决因考虑“真实”部件或组件而产生的复杂问题。遗传算法与容差分析程序包的结合提供了一种在并行或分布式计算网络上高效运行的有吸引力的替代方案。初步考虑离散公差极限优化。还将研究修改公称尺寸和装配顺序的适用性。

A computational design tool will be developed which will allow for optimal tolerance allocation for mechanical and electrical components. The basic approach is to couple a nontraditional optimization method with a Monte Carlo based tolerance analysis code. The ability to allocate tolerances in an optimal fashion will allow an installed capital base to be utilized in the most productive fashion. A successful application of the technique will have a dramatic impact on reducing manufacturing cost and product cycle times as well as increasing productivity, quality and customer satisfaction. Current tolerance analysis used in industry does not provide the ability to allocate tolerances in an optimal fashion. Traditional nonlinear programming methods are not robust enough to solve the complex problem resulting from the consideration of a "real" component or assembly. The combination of the genetic algorithm with a tolerance analysis package offers an attractive alternative which will run efficiently on a parallel or distributed computing network. Initial consideration will be placed on discrete tolerance limit optimization. The applicability to modifying nominal dimensions and assembly sequence will also be investigated.