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A mathematical maintenance model for a production system subject to deterioration according to a stochastic geometric process
by
Naderkhani, Farnoosh
, Rasay, Hasan
, Azizi, Fariba
in
Comparative studies
/ Competition
/ Competitive advantage
/ Cyber-physical systems
/ Failure mechanisms
/ Military applications
/ OEM
/ Operations research
/ Preventive maintenance
/ Random variables
/ Repair
/ Safety critical
2024
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A mathematical maintenance model for a production system subject to deterioration according to a stochastic geometric process
by
Naderkhani, Farnoosh
, Rasay, Hasan
, Azizi, Fariba
in
Comparative studies
/ Competition
/ Competitive advantage
/ Cyber-physical systems
/ Failure mechanisms
/ Military applications
/ OEM
/ Operations research
/ Preventive maintenance
/ Random variables
/ Repair
/ Safety critical
2024
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Do you wish to request the book?
A mathematical maintenance model for a production system subject to deterioration according to a stochastic geometric process
by
Naderkhani, Farnoosh
, Rasay, Hasan
, Azizi, Fariba
in
Comparative studies
/ Competition
/ Competitive advantage
/ Cyber-physical systems
/ Failure mechanisms
/ Military applications
/ OEM
/ Operations research
/ Preventive maintenance
/ Random variables
/ Repair
/ Safety critical
2024
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A mathematical maintenance model for a production system subject to deterioration according to a stochastic geometric process
Journal Article
A mathematical maintenance model for a production system subject to deterioration according to a stochastic geometric process
2024
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Overview
Given the deteriorative nature of industrial systems, implementation of advanced Preventive Maintenance (PM) strategies becomes of paramount importance to cope with the maintenance needs of ever-changing complex industrial and safety-critical systems. Conventionally, PM approaches are developed based on the perfect maintenance assumption, i.e., the underlying system is renewed to the as-good-as-new state after each preventive repair, or corrective maintenance action. Such an assumption, however, is not realistic in applications such as military machinery, power generation networks, and Cyber-Physical Systems (CPS), rendering conventional PM strategies impractical. In such application domains, it is not feasible to perform all the required maintenance actions during the available time leading to imperfect maintenance. Overlooking imperfect maintenance is critically problematic as it further deteriorates the reliability of the underlying system shortening its life span. Therefore, it is critical to perform optimal maintenance decisions under imperfect maintenance assumptions. While Geometric Process (GP) is broadly used for imperfect maintenance modeling and analysis of repairable systems, its utilization to describe the failure mechanism of production systems/processes is still in its infancy. Existing works, typically, consider restrictive assumptions to simplify the maintenance models, which limits their applicability. This paper addresses this gap and proposes a rigorous mathematical model without the incorporation of restrictive assumptions. More specifically, we consider a system for which the operational states are observable through inspections performed at specified time points and only the failure state is immediately observable. Upon the inspection, if the system is found to be in a partially-failed state, a Minor Repair (MIR) action is conducted. The effect of MIR is imperfect and MIR can only be conducted a maximum number of N times during a production cycle. After performing a MIR action, the failure mechanism of the system changes according to a stochastic decreasing GP. When the system enters the failure state, a Major Repair (MJR) action is conducted, which brings the system back to the as-good-as-new state. A comprehensive set of numerical examples, comparative studies, and sensitivity analyses are conducted to evaluate the efficacy of the proposed maintenance policy.
Publisher
Springer Nature B.V
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