A decision making model for maintenance strategy: A combined approach analytic hierarchy process (AHP) and fuzzy logic

This research aims to compare two tools for decision makers that intend to support decision for the selection of most appropriate maintenance strategy in oil and gas plants. The analytic hierarchy process (AHP) decision making model proposed based on case study that investigate implementation of an integrated condition based maintenance strategy for oil and gas industry. Moreover fuzzy set theory employed for reducing the vagueness associated with manager preferences. The oilfield developed by British Petroleum (BP) and was brought on stream in June 1990 with the production of 95000 barrels of stabilised crude oil. 670 tonnes of LPG and 16 million standard cubic feet of sales gas in which the associate gas is then fractionated, the methane and ethane are exported as sales gas directly into the grid, while the propane and butane are liquefied and transported by rail tanker. Since operations began, the traditional cost benefit analysis was considered to evaluate the appropriateness of condition based monitoring strategy for rotating equipment.The proposed fuzzy AHP models deal with the uncertainty related to imprecise judgments of decision makers and experts by quantifying the qualitative data obtained through AHP questioners to fuzzy interface model. An optimal maintenance strategy obtained for the BP process plant which can effectively improve availability and reliability levels of plants equipment. The research output suggest that not only CBM can improves the safety of plant but also investment in upgrading the skill of operators could effectively improves the level of safety in the process plant.