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MMAPs to Model Complex Multi-State Systems with Vacation Policies in the Repair Facility

[PDF] 04_Juan (16).pdf (637.2Kb)
Identificadores
URI: https://hdl.handle.net/10481/99370
DOI: 10.13052/jrss0974-8024.1524
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Author
Ruiz Castro, Juan Eloy; Acal González, Christian José
Date
2022-07-22
Referencia bibliográfica
Journal of Reliability and Statistical Studies, Vol. 15, Issue 2 (2022), 473–504
Sponsorship
This paper is supported by the project FQM-307 of the Government of Andalusia (Spain), by the project PID2020-113961GB-I00 of the Spanish Ministry of Science and Innovation (also supported by the European Regional Development Fund program, ERDF) and the project A-FQM-66-UGR20 of the Ministry of Knowledge, Research and University, Junta de Andalucía (Spain). Also, the authors acknowledge financial support by the IMAG–María de Maeztu grant CEX2020-001105-M/AEI/10.13039/501100011033
Abstract
Two complex multi-state systems subject to multiple events are built in an algorithmic and computational way by considering phase-type distributions and Markovian arrival processes with marked arrivals. The internal performance of the system is composed of different degradation levels and internal repairable and non-repairable failures can occur. Also, the system is subject to external shocks that may provoke repairable or non-repairable failure. A multiple vacation policy is introduced in the system for the repairperson. Preventive maintenance is included in the system to improve the behaviour. Two types of task may be performed by the repairperson; corrective repair and preventive maintenance. The systems are modelled, the transient and stationary distributions are built and different performance measures are calculated in a matrix-algorithmic form. Cost and rewards are included in the model in a vector matrix way. Several economic measures are worked out and the net reward per unit of time is used to optimize the system. A numerical example shows that the system can be optimized according to the existence of preventive maintenance and the distribution of vacation time. The results have been implemented computationally with Matlab and R (packages: expm, optim).
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