A novel predict-prevention quality control method of multi-stage manufacturing process towards zero defect manufacturing

Li-Ping Zhao; Bo-Hao Li; Yi-Yong Yao

doi:10.1007/s40436-022-00427-9

Advances in Manufacturing ›› 2023, Vol. 11 ›› Issue (2) : 280 -294. DOI: 10.1007/s40436-022-00427-9

Article

A novel predict-prevention quality control method of multi-stage manufacturing process towards zero defect manufacturing

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^a lipingzh@mail.xjtu.edu.cn

Li-Ping Zhao received the Ph.D. degree in mechanical manufacture and automation from the School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China, in 1996. Currently, she is a professor with the School of Mechanical Engineering, Xi’an Jiaotong University. Her research interests include quality control engineering, manufacturing system modeling, and integrating computer aided design/computer aided process planning/computer aided engineering (CAD/CAPP/CAE).

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Bo-Hao Li received the B.S. degree in Mechanical engineering and automation from School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China, in 2016. Currently, he is pursuing the Ph.D. degree at the School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an. His research interests include manufacturing system modeling and machining process quality prediction.

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Yi-Yong Yao received the Ph.D. degree in mechatronic engineering from the School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, in 2001. He is currently an associate professor with the School of Mechanical Engineering, Xi’an Jiaotong University. His research interests include intelligent control technology, mechatronics, and product security technology.

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Abstract

Zero defection manufacturing (ZDM) is the pursuit of the manufacturing industry. However, there is a lack of the implementation method of ZDM in the multi-stage manufacturing process (MMP). Implementing ZDM and controlling product quality in MMP remains an urgent problem in intelligent manufacturing. A novel predict-prevention quality control method in MMP towards ZDM is proposed, including quality characteristics monitoring, key quality characteristics prediction, and assembly quality optimization. The stability of the quality characteristics is detected by analyzing the distribution of quality characteristics. By considering the correlations between different quality characteristics, a deep supervised long-short term memory (SLSTM) prediction network is built for time series prediction of quality characteristics. A long-short term memory-genetic algorithm (LSTM-GA) network is proposed to optimize the assembly quality. By utilizing the proposed quality control method in MMP, unqualified products can be avoided, and ZDM of MMP is implemented. Extensive empirical evaluations on the MMP of compressors validate the applicability and practicability of the proposed method.

Keywords

Zero defection manufacturing (ZDM) / Multi-stage manufacturing process (MMP) / Moving window / Deep supervised long-short term memory (SLSTM) network / Assembly quality optimization

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Li-Ping Zhao, Bo-Hao Li, Yi-Yong Yao. A novel predict-prevention quality control method of multi-stage manufacturing process towards zero defect manufacturing. Advances in Manufacturing, 2023, 11(2): 280-294 DOI:10.1007/s40436-022-00427-9