Optimal allocation of statistical tolerance indices by genetic algorithms

被引：3

作者：

Otsuka, A. ^{[1
]}

Nagata, F. ^{[1
]}

机构：

[1] 1-1-1 Daigaku Dori, Sanyo Onoda, Yamaguchi 7560884, Japan

来源：

ARTIFICIAL LIFE AND ROBOTICS | 2014年 / 19卷 / 03期

关键词：

Product performance; Statistical tolerance index; Process capability index; Tolerance allocation; Genetic algorithms;

D O I：

10.1007/s10015-014-0157-x

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

Recently, process capabilities for machining and measurement in manufacturing industries have been increasing in response to customer demand for improved product performance, and these requirements will continue to grow as technology advances. To satisfy this consumer demand, we have studied a tolerance method using statistical tolerance indices to specify the limitation of process capability indices. In this paper, we propose a method of allocating statistical tolerance indices using genetic algorithms. The proposed method is applied to a product model comprising five parts, assembled in linear combination, to confirm its effectiveness.

引用

页码：227 / 232

页数：6