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 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 gruvi golden lager 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 read more 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.