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Integrated predictive maintenance strategy for manufacturing systems by combining quality control and mission reliability analysis

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  • Yihai He
  • Changchao Gu
  • Zhaoxiang Chen
  • Xiao Han

Abstract

Predictive maintenance (PdM) is an effective means to eliminate potential failures, ensure stable equipment operation and improve the mission reliability of manufacturing systems and the quality of products, which is the premise of intelligent manufacturing. Therefore, an integrated PdM strategy considering product quality level and mission reliability state is proposed regarding the intelligent manufacturing philosophy of ‘prediction and manufacturing’. First, the key process variables are identified and integrated into the evaluation of the equipment degradation state. Second, the quality deviation index is defined to describe the quality of the product quantitatively according to the co-effect of manufacturing system component reliability and product quality in the quality–reliability chain. Third, to achieve changeable production task demands, mission reliability is defined to characterise the equipment production states comprehensively. The optimal integrated PdM strategy, which combines quality control and mission reliability analysis, is obtained by minimising the total cost. Finally, a case study on decision-making with the integrated PdM strategy for a cylinder head manufacturing system is presented to validate the effectiveness of the proposed method. The final results shows that proposed method achieves approximately 26.02 and 20.54% cost improvement over periodic preventive maintenance and conventional condition-based maintenance respectively.

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  • Yihai He & Changchao Gu & Zhaoxiang Chen & Xiao Han, 2017. "Integrated predictive maintenance strategy for manufacturing systems by combining quality control and mission reliability analysis," International Journal of Production Research, Taylor & Francis Journals, vol. 55(19), pages 5841-5862, October.
    • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:19:p:5841-5862
    DOI: 10.1080/00207543.2017.1346843
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    Cited by:

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    3. Liao, Ruoyu & He, Yihai & Feng, Tianyu & Yang, Xiuzhen & Dai, Wei & Zhang, Weifang, 2023. "Mission reliability-driven risk-based predictive maintenance approach of multistate manufacturing system," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    4. Zhang, Tian & Homri, Lazhar & Dantan, Jean-Yves & Siadat, Ali, 2023. "Models for reliability assessment of reconfigurable manufacturing system regarding configuration orders," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    5. Yang, Xiuzhen & He, Yihai & Liao, Ruoyu & Cai, Yuqi & Ai, Jun, 2022. "Integrated mission reliability modeling based on extended quality state task network for intelligent multistate manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    6. Sinisterra, Wilfrido Quiñones & Lima, Victor Hugo Resende & Cavalcante, Cristiano Alexandre Virginio & Aribisala, Adetoye Ayokunle, 2023. "A delay-time model to integrate the sequence of resumable jobs, inspection policy, and quality for a single-component system," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    7. Thirupathi Samala & Vijaya Kumar Manupati & Maria Leonilde R. Varela & Goran Putnik, 2021. "Investigation of Degradation and Upgradation Models for Flexible Unit Systems: A Systematic Literature Review," Future Internet, MDPI, vol. 13(3), pages 1-18, February.
    8. Shi, Haohao & Zhang, Ji & Zio, Enrico & Zhao, Xufeng, 2023. "Opportunistic maintenance policies for multi-machine production systems with quality and availability improvement," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    9. Yue-Yi Zhang & Han-Ting Zhou & Ijaz Younis & Li Zhou, 2021. "Coupling Coordination Analysis of Technological Innovation, Standards, and Quality: Evidence From China," SAGE Open, , vol. 11(3), pages 21582440211, July.
    10. Zhao, Xian & Li, Rong & Cao, Shuai & Qiu, Qingan, 2023. "Joint modeling of loading and mission abort policies for systems operating in dynamic environments," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    11. He, Yihai & Zhao, Yixiao & Han, Xiao & Zhou, Di & Wang, Wenzhuo, 2020. "Functional risk-oriented health prognosis approach for intelligent manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    12. Yixiao Zhao & Yihai He & Fengdi Liu & Xiao Han & Anqi Zhang & Di Zhou & Yao Li, 2020. "Operational risk modeling based on operational data fusion for multi-state manufacturing systems," Journal of Risk and Reliability, , vol. 234(2), pages 407-421, April.
    13. Li, Yao & He, Yihai & Liao, Ruoyu & Zheng, Xin & Dai, Wei, 2022. "Integrated predictive maintenance approach for multistate manufacturing system considering geometric and non-geometric defects of products," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    14. Wang, Lin & Lu, Zhiqiang & Ren, Yifei, 2020. "Joint production control and maintenance policy for a serial system with quality deterioration and stochastic demand," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    15. Ye, Zhenggeng & Cai, Zhiqiang & Yang, Hui & Si, Shubin & Zhou, Fuli, 2023. "Joint optimization of maintenance and quality inspection for manufacturing networks based on deep reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    16. Cheng, Guoqing & Li, Ling, 2020. "Joint optimization of production, quality control and maintenance for serial-parallel multistage production systems," Reliability Engineering and System Safety, Elsevier, vol. 204(C).

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