A new approach to managing maintenance and repairs of offshore oil and gas platforms using fuzzy-DEMATEL
Year: 2025
Type: article
Abstract: The maintenance and repair of offshore oil and gas platforms are of critical importance in ensuring operational efficiency, safety, and environmental protection. Conventional maintenance strategies frequently encounter difficulties in addressing the intricacies and uncertainties intrinsic to offshore environments, resulting in elevated downtime and augmented operational expenditures. This study proposes a novel approach that integrates fuzzy logic with the DEMATEL (Decision-Making Trial and Evaluation Laboratory) method, termed fuzzy-DEMATEL, with a view to enhancing maintenance management in offshore settings. The proposed methodology employs fuzzy logic to effectively capture the uncertainties associated with various maintenance factors, while DEMATEL provides a systematic framework for analyzing and visualizing the relationships between these factors. The objective of this research is to develop a comprehensive maintenance management framework that prioritizes maintenance activities based on a holistic assessment of equipment reliability, environmental conditions, and operational constraints. A comprehensive review of the extant literature and a series of case studies were undertaken in order to evaluate the effectiveness of the fuzzy-DEMATEL approach. The results obtained demonstrate the potential of this approach to improve decision-making processes and optimize maintenance strategies in offshore oil and gas platforms. The results obtained in this study indicate that intelligence (C10) has the highest degree of influence, while maintenance and repair management (C1) exhibit a very high level of influence. Furthermore, (C1) exhibits the highest degree of interaction with other criteria. The findings of this study contribute to the advancement of maintenance management practices in the industry, paving the way for more sustainable and efficient operations.
Authors: Dehghani, Reza, Sadeghian, Abolfazl, Dehghan Dehnavi, Hassan, Rabbani, Mozhde, Honari, Mohammad Taghi Honari
Institution: Islamic Azad University, Yazd
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7095064627
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