An advanced decision-making model for evaluating manufacturing plant locations using fuzzy inference system. (1st April 2022)

• Record Type: Journal Article
• Authors: Paul, Sanjoy Kumar; Chowdhury, Priyabrata; Ahsan, Kamrul; Ali, Syed Mithun; Kabir, Golam
• Is Part Of: Expert systems with applications. Volume 191(2022)
• Publication Date: 2022-04-01
• Subjects: Manufacturing plant location -- Intelligent decision-making -- Fuzzy inference system -- Multi-criteria decision-making; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2021.116378
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: Manufacturing plant locations are evaluated. An advanced and intelligent decision-making framework is developed. Qualitative Delphi and quantitative fuzzy inference system are integrated. A real-life case is presented to demonstrate the applicability of the framework. Abstract: Locating a manufacturing plant is a complex multi-criteria decision-making problem as it involves many tangible and intangible criteria. This paper contributes to the existing theory by integrating a qualitative Delphi and a quantitative fuzzy inference system (FIS) for developing an advanced and intelligent decision-making framework for evaluating manufacturing plant locations. The Delphi method is used to identify the most significant manufacturing plant location selection criteria. The identified major criteria are used to develop an advanced FIS framework to evaluate potential manufacturing plant locations. A real-life case is presented to demonstrate the applicability of the developed decision-making framework. This paper contributes to the literature by developing an advanced decision-making framework for evaluating manufacturing plant locations and by integrating qualitative Delphi and quantitative FIS, which can help industrial managers locate their manufacturing plant locations intelligently and accurately.