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Algorithmic modelling of a complex redundant multi-state system subject to multiple events, preventive maintenance, loss of units and a multiple vacation policy through a MMAP

[PDF] MATCOM-2025-JERC-HAZC.pdf (1.651Mb)
Identificadores
URI: https://hdl.handle.net/10481/99403
DOI: 10.1016/j.matcom.2024.11.005
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Autor
Ruiz Castro, Juan Eloy; Zapata Ceballos, Hugo Alaín
Fecha
2025-04
Referencia bibliográfica
Mathematics and Computers in Simulation, Volume 230, April 2025, Pages 165-192
Patrocinador
This paper is partially supported by the project FQM-307 of the Government of Andalusia (Spain) and by the project PID2023-149087NB-I00 of the Spanish Ministry of Science and Innovation (also supported by the FEDER programme). Additionally, the first author would like to express their gratitude for financial support by the IMAG–María de Maeztu grant CEX2020-001105-M/AEI/10.13039/501100011033
Resumen
A complex multi-state redundant system undergoing preventive maintenance and experiencing multiple events is being considered in a continuous time frame. The online unit is susceptible to various types of failures, both internal and external in nature, with multiple degradation levels present, both internally and externally. Random inspections are continuously monitoring these degradation levels, and if they reach a critical state, the unit is directed to a repair facility for preventive maintenance. The maintenance place is managed by a repairperson, who follows a multiple vacation policy dependent on the operational status of the units. The repairperson is responsible for two primary tasks: corrective repair and preventive maintenance. The time durations within the system follow phase-type distributions, and the model is constructed utilizing Markovian Arrival Processes with marked arrivals. A variety of performance measures, including transient and stationary distributions, are calculated using matrix-analytic methods. This methodology allows for the representation of significant outcomes and the general behavior of the system in a matrix-algorithmic structure. To enhance the model's efficiency, both costs and rewards are incorporated into the analysis. A numerical example is presented to showcase the model's flexibility and effectiveness in real-world applications.
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