Developing Turnaround Maintenance (TAM) Model to Optimize TAM Performance Based on the Critical Static Equipment (CSE) of GAS Plants

Abstract

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.