Cheikh Khamiss, Boudi E L Mostapha, Rabi Rabi, Mokhliss Hamza
Department of Mechanical Engineering, Energetic team,Mechanical and Industrial Systems (EMISys), Mohammadia School of Engineers, Mohammed V University, Rabat, Morocco.
Department of Physics (LPM-ERM), Faculty of Sciences and Techniques, Sultan Moulay Sliman University, B.P.523, Beni-Mellal 23000, Morocco.
MethodsX. 2024 Jun 29;13:102819. doi: 10.1016/j.mex.2024.102819. eCollection 2024 Dec.
This study aims to develop comprehensive maintenance strategies tailored to enhance the dependability, performance, and lifespan of critical assets within industrial and organizational settings. By integrating proactive, preventive, predictive, and corrective maintenance tactics, our strategy seeks to minimize downtime, reduce costs, and optimize asset performance. Drawing from extensive case studies across various industrial sectors, our research utilizes robust data analysis to inform strategy development. We employ mathematical cost models and simulations using the Monte Carlo Method in MATLAB to evaluate the performance and robustness of different maintenance strategies, including time-based and condition-based approaches. Our findings demonstrate that a holistic maintenance approach significantly improves operational efficiency and asset longevity. Specifically, our analysis reveals that integrated maintenance strategies lead to reduced downtime, lower maintenance costs, and enhanced asset reliability. Policy implications of our research suggest that organizations should adopt integrated maintenance strategies to enhance asset reliability and performance, ultimately achieving sustained operational excellence. By emphasizing the importance of proactive maintenance measures alongside traditional reactive approaches, organizations can effectively manage their critical assets, leading to improved operational outcomes and long-term success.-Integration of proactive, preventive, predictive, and corrective maintenance tactics-Evaluation of performance and robustness through mathematical cost models-Application of the Monte Carlo Method in MATLAB for comparative analysis.
本研究旨在制定全面的维护策略，以提高工业和组织环境中关键资产的可靠性、性能和使用寿命。通过整合主动、预防、预测和纠正性维护策略，我们的策略旨在最大限度地减少停机时间、降低成本并优化资产性能。基于对各工业部门大量案例研究，我们的研究利用强大的数据分析为策略制定提供依据。我们使用数学成本模型并在MATLAB中运用蒙特卡罗方法进行模拟，以评估不同维护策略（包括基于时间和基于状态的方法）的性能和稳健性。我们的研究结果表明，整体维护方法可显著提高运营效率和资产寿命。具体而言，我们的分析表明，综合维护策略可减少停机时间、降低维护成本并提高资产可靠性。我们研究的政策含义表明，组织应采用综合维护策略来提高资产可靠性和性能，最终实现持续卓越运营。通过强调主动维护措施与传统被动方法同样重要，组织可以有效管理其关键资产，从而改善运营成果并取得长期成功。
整合主动、预防、预测和纠正性维护策略
通过数学成本模型评估性能和稳健性
在MATLAB中应用蒙特卡罗方法进行比较分析
