Deviation propagation and reduction analysis for multi-operational machining processes

Liang Ju, Dongfeng Wang, Jiang Ping
{"title":"Deviation propagation and reduction analysis for multi-operational machining processes","authors":"Liang Ju, Dongfeng Wang, Jiang Ping","doi":"10.1109/ICEMI.2011.6037790","DOIUrl":null,"url":null,"abstract":"Product dimensional quality has been one of the most important challenges for machining processes. However, current practice in multi-operational machining is a monitoring or inspection oriented measurement strategy which could not provide solutions for deviation reduction while deviation propagation and compensation are taken into account. While the deviation of some quality characteristic is not satisfactory and could not be controlled in the last operation, a partial least squares regression method is proposed to set up the relations between upstream operations and the last one. The regression result helps engineers to identify key processes with respect to their impacts on the last one, and to figure out possible solutions to reduce the deviation and thus makes the quality characteristic achieve the acceptable level. An industrial case is presented to illustrate our proposed methodology.","PeriodicalId":321964,"journal":{"name":"IEEE 2011 10th International Conference on Electronic Measurement & Instruments","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE 2011 10th International Conference on Electronic Measurement & Instruments","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEMI.2011.6037790","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Product dimensional quality has been one of the most important challenges for machining processes. However, current practice in multi-operational machining is a monitoring or inspection oriented measurement strategy which could not provide solutions for deviation reduction while deviation propagation and compensation are taken into account. While the deviation of some quality characteristic is not satisfactory and could not be controlled in the last operation, a partial least squares regression method is proposed to set up the relations between upstream operations and the last one. The regression result helps engineers to identify key processes with respect to their impacts on the last one, and to figure out possible solutions to reduce the deviation and thus makes the quality characteristic achieve the acceptable level. An industrial case is presented to illustrate our proposed methodology.
多工序加工过程的偏差传播与减小分析
产品尺寸质量一直是机械加工过程中最重要的挑战之一。然而,目前在多工序加工中采用的是一种以监测或检测为导向的测量策略,在考虑误差传播和补偿的情况下,无法为减小误差提供解决方案。针对上一道工序中某些质量特性偏差不理想,无法控制的问题,提出了用偏最小二乘回归方法建立上游工序与上一道工序之间的关系。回归结果有助于工程师识别关键过程对最后一个过程的影响,并找出可能的解决方案来减少偏差,从而使质量特性达到可接受的水平。以一个工业案例来说明我们提出的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信