Fuzzy AHP approach to selection problems in process engineering involving quantitative and qualitative aspects |
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| Institution: | 1. Chemical Engineering Department, De La Salle University, 2401 Taft Avenue, Malate, Manila, 1004, Philippines;2. Center for Engineering and Sustainable Development Research, De La Salle University, Manila, 1004, Philippines;1. Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan.;1. Australian Rivers Institute and School of Environment, Griffith University Gold Coast Campus, Southport, Qld 4222, Australia;2. Beijing Zhongqi Anxin Environmental Science & Technology Co., Ltd., Beijing 100053, China;3. State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, 8 Dayangfang, Beiyuan, Anwai, Beijing 100012, PR China;4. Development Centre of Ministry of Environmental Protection, Beijing 100001, PR China;5. State Key Laboratory of Organic Geochemistry, Guangdong Institute of Eco-Environmental and Soil Sciences, Chinese Academy of Science, P.O. Box 1131, Wushan, Guangzhou 510640, PR China;6. Department of Environment and Energy Engineering, Anhui Jianzhu University, Hefei, Anhui 230001, PR China;1. Griffith Centre for Coastal Management, Griffith University, QLD 4222, Australia;2. Australian River Institute, Griffith University, QLD 4222, Australia;3. Gold Coast City Council, Gold Coast, QLD 4211, Australia |
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| Abstract: | Selection problems are common in process engineering. In most cases, it is necessary to rank alternatives based on multiple criteria (e.g., cost, safety, environmental impact), which are often conflicting. In addition, some criteria may be fundamentally difficult to quantify due to data scarcity, in which case subjective assessments need to be used as a proxy. Decision analysis tools such as the analytic hierarchy process (AHP) are useful to ensure decision-making is done rationally. In this work, we propose a fuzzy AHP variant, wherein pairwise comparison of decision elements by domain experts is expressed with triangular fuzzy numbers. This approach allows the degree of confidence of the expert to be quantified explicitly; it also allows inconsistencies in judgment to be reconciled within the bounds of the fuzzy numbers to generate reasonable values for the weighting factors. We demonstrate the methodology on three case studies, involving the comparison of different types of chlor-alkali electrolytic cells, CO2 capture techniques in cement plants and wastewater treatment options for municipal wastewater. |
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| Keywords: | Decision analysis Fuzzy AHP Process safety Electrolysis Wastewater treatment |
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