NDLI: Deviation propagation and reduction analysis for multi-operational machining processes

Content Provider	IEEE Xplore Digital Library
Author	Liang Ju Wang Dongfeng Jiang Ping
Copyright Year	2011
Description	Author affiliation: Beijing Aerospace Control Center, China (Liang Ju) \|\| Beijing Special Engineering Design and Research Institute, China (Wang Dongfeng) \|\| Department of System Engineering, College of Information Systems and Management, National University of Defense Technology, Changsha, Hunan, China (Jiang Ping)
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.
Starting Page	171
Ending Page	175
File Size	109627
Page Count	5
File Format	PDF
ISBN	9781424481583
e-ISBN	9781424481613
DOI	10.1109/ICEMI.2011.6037790
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Correlation Quality characteristic Instruments Process control Machining Educational institutions Multi-operational machining process Matrix decomposition Deviation Partial least squares Monitoring
Content Type	Text
Resource Type	Article

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