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A continuous‐time Markov chain model for redundancy allocation problem: An economic analysis
Author(s) -
Tohidi Hossein,
Chavoshi Saeed,
Bahmaninezhad Azadeh
Publication year - 2019
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2480
Subject(s) - spare part , markov chain , reliability engineering , computer science , redundancy (engineering) , markov decision process , mean time between failures , profit (economics) , reliability (semiconductor) , net present value , operations research , markov model , investment (military) , markov process , mathematical optimization , failure rate , engineering , operations management , economics , mathematics , production (economics) , statistics , microeconomics , law , power (physics) , quantum mechanics , machine learning , political science , physics , politics
Reliability of an engineering system can be improved by investing on redundant (spare) parts. However, the cost‐efficiency of such an investment is a significant concern that needs to be taken into consideration in practice. To do so, a continuous‐time Markov chain (CTMC) model is presented in this paper to analyze the system's reliability by allocating redundant components. The developed model can also capture the system's repair and failure conditions by defining appropriate states in CTMC. Subsequently, the net present value (NPV) approach is utilized for a variety of scenarios to investigate the effectiveness of investment on spare parts using the break‐even point (BEP) analysis. Afterwards, a comprehensive analysis is carried out to examine the impact of input parameters including interest rate, initial cost of investment, and periodic profit on the decision making process to find the optimal number of spare parts.