Mission Reliability-Oriented Selective Maintenance Optimization for Intelligent Multistate Manufacturing Systems With Uncertain Maintenance Quality

Mission Reliability-Oriented Selective Maintenance Optimization for Intelligent Multistate Manufacturing Systems With Uncertain Maintenance Quality

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Selective maintenance is widely used as a reliability-centered maintenance strategy due to the limited maintenance resources.However, existing selective honeywell pa404a1009 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 gauze fabric by the bolt 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.