Title: Wavelet-based process quality monitoring and diagnosing

Authors: Daoyu Liu, Pingyu Jiang

Addresses: State Key Laboratory for Manufacturing Systems Engineering, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China. ' State Key Laboratory for Manufacturing Systems Engineering, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China

Abstract: In order to improve machining quality, this paper presents an integrated process quality monitoring and diagnosing methodology for machining process. Dimensional quality characteristic of work-piece is first monitored by wavelet-based SPC charts. And then, power spectrum analysis is used to extract abnormal feature signal if abnormal change is detected. Basing on this, a correlated model is established to calculate correlation coefficient between abnormal change and its fault sources, and synthesised diagnosis is provided to determine the importance level of these fault sources. At last, a running example is given to verify the proposed methodology.

Keywords: wavelet transform; statistical process control; SPC; correlation analysis; fault source identification; process quality; process monitoring; fault diagnosis; machining quality; control charts.

DOI: 10.1504/IJMPT.2008.019779

International Journal of Materials and Product Technology, 2008 Vol.33 No.1/2, pp.153 - 169

Published online: 30 Jul 2008 *

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