arrow
返回

Quality control in machining using order statistics

delete2018-02-01
delete6
delete
OA
AI
A
Abdoulaye Diamoutene
F
Farid Noureddine
B
Bernard Kamsu-Foguem *
D
Diakarya Barro
DOI:10.1016/j.measurement.2017.11.036delete
delete原文链接
delete分享
delete收藏
查看原文
摘要

摘要

En 中文
The quality of surface roughness for machined parts is essential in the manufacturing process. The cutting tool plays an important role in the roughness of the machined parts. The process of determining the number of tolerant faults is problematic; this is due to the fact that the behaviour of the cutting tool is random. In this paper, we use an approach based on order statistics to study the construction of functional and reliability characteristic for the faults tolerant machined parts in each five batch of ten machined parts. Our experiments show that the number of faulty machined parts will not exceed two and the distribution of the minimum gives the best interval of the surface roughness. We have shown that the distribution of extreme order statistics plays an important role in determining the lower and upper limits of the roughness measurements depending on the reliability of the cutting tool.
Keyword:
Order statistics
Extreme value theory
Quality control in machining
Surface roughness measurements
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Measurement 封面图
Measurement
IF:
5.6
论文数:
2.0W
被引数:
5.4W

机构

U
universite de toulouse
学者数:
3.5W
论文数: 2.7W
被引数: 37
引用论文

引用论文

Drone-Mounted Lidar Survey of Maya Settlement and Landscape
err2019-08-27
err0
PREAI
errTimothy M. Murtha; Eben N. Broadbent; Charles Golden; Andrew Scherer; Whittaker Schroder; Ben Wilkinson; Angélica Almeyda Zambrano
err分享
err收藏
err分享
err收藏
没有更多内容