Title:Mission reliability-oriented selective maintenance optimization for intelligent multistate manufacturing systems with uncertain maintenance quality.

Fulltext:https://ieeexplore.ieee.org/document/8789407
Authors:Zhaoxiang Chen,Yihai He,Yixiao Zhao, Xiao Han, Fengdi Liu,Di Zhou,Wenzhuo Wang.
Journal :IEEE Access.
SCI Impact factor:4.098(Q1) .
Published date:August6,2019.

Abstract:
Selective maintenance is widely used as a reliability-centered maintenance strategy due to the limited maintenance resources. However, existing selective maintenance studies only consider basic reliability, which cannot systematically describe the operating mechanism of a multistate system, thereby resulting in the inability to obtain an optimal maintenance strategy. Moreover, intelligent manufacturing systems are highly representative of typical multistate industrial systems. In this study, a mission reliability-oriented selective maintenance optimization model for intelligent manufacturing systems that considers the uncertain maintenance effect was proposed. First, a new connotation and modeling method for mission reliability based on multistate system theory was presented to comprehensively characterize the operating mechanism of intelligent manufacturing systems. Second, a quantitative model between maintenance resources and quality based on real-time data was established to reflect the uncertain characteristics caused by repairmen and tools. Third, a selective maintenance decision model of a multistate manufacturing system was developed under the constraints of maintenance cost and time. This constraint combination optimization problem was solved using the particle swarm optimization algorithm. Finally, a case study of selective maintenance optimization for a cylinder head manufacturing system was presented to verify the proposed method.