جلد 35، شماره 3 - ( 6-1403 )
جلد 35 شماره 3 صفحات 62-44 |
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cheikh K, Boudi E M, Mokhliss H, Rabi R. Development and Optimization of Maintenance Using the Monte Carlo Method. IJIEPR 2024; 35 (3) :44-62
URL: http://ijiepr.iust.ac.ir/article-1-1994-fa.html
URL: http://ijiepr.iust.ac.ir/article-1-1994-fa.html
Development and Optimization of Maintenance Using the Monte Carlo Method. نشریه بین المللی مهندسی صنایع و تحقیقات تولید. 1403; 35 (3) :44-62
چکیده: (1064 مشاهده)
Maintenance plan efficacy traditionally prioritizes long-term predicted maintenance cost rates, emphasizing performance-centric approaches. However, such criteria often neglect the fluctuation in maintenance costs over renewal cycles, posing challenges from a risk management perspective. This study challenges conventional solutions by integrating both performance and robustness considerations to offer more suitable maintenance options.
The study evaluates two representative maintenance approaches: a block replacement strategy and a periodic inspection and replacement strategy. It introduces novel metrics to assess these approaches, including long-term expected maintenance cost rate as a performance metric and variance of maintenance cost per renewal cycle as a robustness metric.
Mathematical models based on the homogeneous Gamma degradation process and probability theory are employed to quantify these strategies. Comparative analysis reveals that while higher-performing strategies may demonstrate cost efficiency over the long term, they also entail greater risk due to potential cost variability across renewal cycles.
The study underscores the necessity for a comprehensive evaluation that balances performance and resilience in maintenance decision-making. By leveraging the Monte Carlo Method, this research offers a critical appraisal of maintenance strategies, aiming to enhance decision-making frameworks with insights that integrate performance and robustness considerations.
The study evaluates two representative maintenance approaches: a block replacement strategy and a periodic inspection and replacement strategy. It introduces novel metrics to assess these approaches, including long-term expected maintenance cost rate as a performance metric and variance of maintenance cost per renewal cycle as a robustness metric.
Mathematical models based on the homogeneous Gamma degradation process and probability theory are employed to quantify these strategies. Comparative analysis reveals that while higher-performing strategies may demonstrate cost efficiency over the long term, they also entail greater risk due to potential cost variability across renewal cycles.
The study underscores the necessity for a comprehensive evaluation that balances performance and resilience in maintenance decision-making. By leveraging the Monte Carlo Method, this research offers a critical appraisal of maintenance strategies, aiming to enhance decision-making frameworks with insights that integrate performance and robustness considerations.
نوع مطالعه: پژوهشي |
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قابلیت اطمینان
دریافت: 1402/12/11 | پذیرش: 1403/4/6 | انتشار: 1403/6/28
دریافت: 1402/12/11 | پذیرش: 1403/4/6 | انتشار: 1403/6/28
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