Reliability modeling for failure correlations to a CNC lathe subsystem based on Pagerank Algorithm

Abstract

The modeling of Computer Numerical Control (CNC) lathes has been constrained by various issues, such as the use of single methods, inaccurate model parameters, and inadequate consideration of subsystem failures. To overcome these challenges, this study proposes a reliability modeling method based on the Pagerank Algorithm for analyzing failure correlations in CNC lathe subsystems. The proposed method involves analyzing the failure correlation between subsystems through failure transfer-directed graph and representing the relationship between subsystems using an adjacency matrix. Based on the fault correlation between subsystem, a reliability model of the CNC lathe subsystem is established, and the Pagerank Algorithm is utilized to optimize the influence degree of each subsystem. To validate the proposed method, field use failure information of CNC lathe is utilized as an example, and the above theoretical modeling is verified and analyzed. Finally, the reliability model based on failure correlation is verified using the D-test value, relative error method, and accurate factor. In comparison to the reliability model without considering failure correlation, the proposed model results in a small relative error and more accurate value.

Keywords:

• failure correlation
• Pagerank Algorithm
• bootstrap
• Friedman test
• subsystem reliability modeling

Acknowledgements

The authors are grateful to the referees for their constructive comments and suggestions, which have improved the manuscript.

Disclosure statement

The authors declared no potential conflicts of interest in the research, authorship, and publication of this article.

Additional information

Funding

This work was supported by the Project of Jilin Provincial Science and Technology Department: Importance Measure of Multi-state Complex System for the Reliability Design of Manufacturing System (20220101238JC).

Notes on contributors

Dongwei Gu

Dongwei Gu received the BS degree in Mechatronic Engineering and Automation Major from the Shijiazhuang Tiedao University, Shijiazhuang, China, in 2006, the MS degree in Mechanical Manufacture and Automation Major from Changchun University of Science and Technology, Changchun, China, in 2010 and the Ph.D. degree in Mechatronic Engineering from Jilin University, Changchun, China, in 2013. In 2019, he is a visiting scholar at Oakland University. His main research interests include importance measures of complex systems, accelerated life reliability test, and system reliability evaluation and maintenance strategy.

Jin Guo

Jin Guo received the BS degree in Mechatronic Engineering from the Changchun University of Technology, Changchun, China, in 2021. He is currently pursuing the MS degree in mechanical engineering at Changchun University of Technology, Changchun, China. His main research interests include theory and method of dynamic resilience assessment and dynamic reliability.

Wenbo Han

Wenbo Han received the BS degree in Mechatronic Engineering from the Changchun University of Technology, Changchun, China, in 2021. He is currently pursuing the MS degree in mechanical engineering at Changchun University of Technology, Changchun, China. His main research interests include theory and method of structural reliability and mechanical reliability.

Song Gao

Song Gao received the BS degree in Electronic Information Engineering from the Central South University, Changsha, China, in 2009, the MS and PhD degrees in Vehicle Engineering from the Dalian University of Technology, Dalian, China, in 2015. From 2015 to now, he was a lecturer at Changchun University of Technology. His main research interests include theory and method of flexible 3D stretch-bending process and rivetless joining process.

Xilu Zhao

Xilu Zhao received the BS degree in mechanics from the Harbin Institute of Technology, Harbin, China, in 1983, the MS degree in Pressure processing from Yanshan University, Yanshan, China, in 1988, and the Ph.D. degree in mechanical physics from Tokyo Institute of Technology, Tokyo, Japan, in 2011. Now he is working at Saitama Institute of Technology, Japan. His research interest covers mechanical optimization design.

Zhen Xu

Zhen Xu received the MS degree in Mechatronic Engineering from the Changchun University of Technology, Changchun, China, in 2021. Now he is working at Shandong Dongyue Polymer Material Co., Ltd.