TY - GEN
T1 - Quality monitor in multi-operation machining processes based on wavelet filtering
AU - Chen, B.
AU - Wang, P.
AU - Zhang, D. H.
AU - Liu, K.
PY - 2012
Y1 - 2012
N2 - The method of quality monitor based on wavelet filtering was proposed to solve the problems of quality control in multi-operation manufacturing processes, whose measurement data contained noise information. The multi-operation machining process quality control model based on the Stream of Variation (SoV) technology was built, which considered the error propagation. Based on this, the method of discrete wavelet transformation was adopted to smooth data and to reduce noise, and then control charts were built by the method of T-square control chart to monitor processes. The average run length (ARL) was adopted to verify the performance of the proposed quality control method. A sample application was developed to illustrate the feasibility and validity of the proposed quality monitor method.
AB - The method of quality monitor based on wavelet filtering was proposed to solve the problems of quality control in multi-operation manufacturing processes, whose measurement data contained noise information. The multi-operation machining process quality control model based on the Stream of Variation (SoV) technology was built, which considered the error propagation. Based on this, the method of discrete wavelet transformation was adopted to smooth data and to reduce noise, and then control charts were built by the method of T-square control chart to monitor processes. The average run length (ARL) was adopted to verify the performance of the proposed quality control method. A sample application was developed to illustrate the feasibility and validity of the proposed quality monitor method.
KW - noise processing
KW - Quality control model
KW - statistical process control
KW - wavelet transformation
UR - http://www.scopus.com/inward/record.url?scp=84903847168&partnerID=8YFLogxK
U2 - 10.1109/IEEM.2012.6838173
DO - 10.1109/IEEM.2012.6838173
M3 - 会议稿件
AN - SCOPUS:84903847168
SN - 9781467329453
T3 - IEEE International Conference on Industrial Engineering and Engineering Management
SP - 2375
EP - 2379
BT - 2012 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2012
PB - IEEE Computer Society
T2 - 2012 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2012
Y2 - 10 December 2012 through 13 December 2012
ER -