Integrated predictive maintenance strategy for manufacturing systems by combining quality control and mission reliability analysis. Issue 19 (2nd October 2017)

• Record Type: Journal Article
• Authors: He, Yihai; Gu, Changchao; Chen, Zhaoxiang; Han, Xiao
• Is Part Of: International journal of production research. Volume 55:Issue 19(2017)
• Page Start: 5841
• Page End: 5862
• Publication Date: 2017-10-02
• Subjects: manufacturing systems -- predictive maintenance (PdM) -- product quality control -- mission reliability analysis -- cost optimisation; Factory management -- Periodicals; 658.57
• DOI: 10.1080/00207543.2017.1346843
• Languages: English
• ISSNs: 0020-7543

Abstract

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.