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Optimizing filtration technology for contamination control in gas processing plants using hesitant q-rung orthopair fuzzy information aggregation

Farid, Hafiz Muhammad Athar; Riaz, Muhammad; Almohsin, Bandar; Marinkovic, Dragan

The natural gas industry faces significant challenges in implementing industrial filtration systems that are both sustainable and maintainable. These are complex issues that necessitate a thorough and pragmatic evaluation to ensure that the technology is both effective and efficient. Due to the increasing importance of environmental sustainability and the need to reduce waste and emissions, the deployment of filtration technology must be carefully evaluated to ensure that it meets these objectives. The goal of this study is to develop a decision-making approach based on Aczel–Alsina (AA) operations, which provide a variety of advantages when dealing with real-world issues. To begin, we’ll go over some new hesitant q-rung orthopair fuzzy set operations such the Aczel–Alsina product, sum, exponent, and scalar multiplication. The suggested AOs are based on AA operations and are used to prioritize industrial filtering technologies while keeping sustainability and maintainability in mind. Several solutions are studied for managing impurities produced by Pakistan’s natural gas sector. After careful evaluation, it has been determined that the cyclo-filter technology is the most viable solution for the natural gas industry. This technology has been chosen due to its adaptability with the regional and local conditions of the study area. By utilizing this technology, policymakers can gain practical insight into process energy and environmental systems and effectively control contamination in the natural gas industry. This decision-making framework offers a new and innovative approach to address sustainability and maintainability challenges in the industry.
Published in: Soft Computing, 10.1007/s00500-023-08588-w, Springer Nature