Strategic Reliability Centered Maintenance Decision Analysis Model Using Fuzzy and Analytic Hierarchy Process for Refinery Valves

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Abstract

Modern industries, particularly oil and gas, necessitate robust maintenance management and optimization for increased profits, plant availability, and maintenance cost reduction. The maintenance strategy is therefore crucial, especially under global economic pressures on equipment reliability. This study examines the present maintenance management practices for refinery valves, critical equipment whose failure can have severe consequences. Many existing models for selecting critical equipment in maintenance management face limitations due to inadequate decision analysis and exclusion of key criteria. This research proposes a strategy model, combining artificial intelligence and multi-criteria decision-making techniques like Fuzzy Logic and Analytical Hierarchy Process, to fill this gap and manage refinery valves' maintenance. Proven by case studies and interviews, the model improves safety, reliability, operational availability and enables operators to monitor their decision consequences. The model can convince asset managers to invest in maintenance initiatives.
针对炼油厂阀门使用模糊和层次分析法建立以可靠性为中心的战略性维护决策分析模型
现代工业,尤其是石油和天然气行业,需要强有力的维护管理和优化,以提高利润、设备可用性和降低维护成本。因此,维护策略至关重要,尤其是在全球经济对设备可靠性施加压力的情况下。本研究探讨了炼油厂阀门的现有维护管理实践,这些关键设备的故障会造成严重后果。由于决策分析不充分和排除了关键标准,许多现有的维护管理关键设备选择模型都存在局限性。本研究提出了一种结合人工智能和多标准决策技术(如模糊逻辑和层次分析法)的策略模型,以填补这一空白并管理炼油厂阀门的维护。通过案例研究和访谈证明,该模型可提高安全性、可靠性和操作可用性,并使操作人员能够监控其决策结果。该模型可以说服资产管理者对维护措施进行投资。
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