基于燃气厂关键静态设备(CSE)的周转维护(TAM)模型优化TAM性能

A. Elwerfalli, M. K. Khan, J. E. Munive-Hernandez
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引用次数: 4

摘要

由于在一定时期内根据工作范围全面关闭工厂进行TAM活动,许多石油和天然气公司遭受了重大的生产损失和更高的维护成本。因此,TAM在人力、物力、时间和成本方面被认为是油气工厂中最大的维护活动。这些工厂通常在工厂正常运行期间进行其他维护策略,如预防性维护,纠正性维护和预测性维护。但是,某些部件或单元在工厂正常运行期间无法进行检查或维护,除非工厂设施由于操作风险而完全关闭。由于操作条件、地理条件和经济因素造成的温度和压力波动、腐蚀、侵蚀、裂缝和疲劳等因素,不同公司的风险有所不同。本文的目的是建立一个与燃气厂TAM持续时间递减和间隔增大相关的TAM优化调度模型。本文提出的方法根据设备的关键和非关键部件分为三个阶段。在第一阶段,从TAM活动中识别并移除非关键设备部件(ne),以进行主动维护。在第二阶段,评估每个选定设备的较高风险,以便根据基于风险的检查(RBI)优先考虑设备的关键部件。第三阶段,对选定的关键部件进行故障概率和可靠性函数的评估。利用TAM模型的开发结果,对全天候连续运行的燃气装置的TAM调度进行了真正的优化,以达到燃气装置可靠性和可用性的理想性能,并降低了由于停产和检修成本而导致的TAM成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Developing Turnaround Maintenance (TAM) Model to Optimize TAM Performance Based on the Critical Static Equipment (CSE) of GAS Plants
Many oil and gas companies have suffered major production losses, and higher cost of maintenance due to the total shutdown of their plants to conduct TAM event during a certain period and according to scope of work. Therefore, TAM is considered the biggest maintenance activity in oil and gas plant in terms of manpower, material, time and cost. These plants usually undergo other maintenance strategies during normal operation of plants such as preventive, corrective and predictive maintenance. However, some components or units cannot be inspected or maintained during normal operation of plant unless plant facilities are a totally shut downed due to operating risks. These risks differ from a company to another due to many factors such as fluctuated temperatures and pressures, corrosion, erosion, cracks and fatigue caused by operating conditions, geographical conditions and economic aspects. The aim of this paper is to develop a TAM model to optimize the TAM scheduling associated with decreasing duration and increasing interval of the TAM of the gas plant. The methodology that this paper presents has three stages based on the critical and non-critical pieces of equipment. At the first stage, identifying and removing Non-critical Equipment pieces (NEs) from TAM activity to proactive maintenance types. During the second stage, the higher risk of each selected equipment is assessed in order to prioritize critical pieces of equipment based on Risk Based Inspection (RBI). At the third stage, failure probability and reliability function for those selected critical pieces of equipment are assessed. The results of development of the TAM model is led to the real optimization of TAM scheduling of gas plants that operated continuously around the clock in order to achieve a desired performance of reliability and availability of the gas plant, and reduce cost of TAM resulting from the production shutdown and cost of inspection and maintenance.
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