Fuzzy-logic-based support tools for initial screening of manufacturing reshoring decisions

• Published in: Industrial management + data systems Vol. 121; no. 5; pp. 965 - 992
• Main Authors: Hilletofth, Per, Sequeira, Movin, Tate, Wendy
• Format: Journal Article
• Language: English
• Published: Wembley Emerald Publishing Limited 30.04.2021; Emerald Group Publishing Limited
• Subjects: Artificial intelligence; Criteria; Decision making; decision support; Decisions; Domains; Fuzzy logic; initial screening; Intelligent industri; Intelligent Industry; Knowledge; Manufacturing; Manufacturing reshoring; Outsourcing; Reshoring; Screening; Subject specialists; Fuzzy logic; Manufacturing reshoring; Initial screening; Decision support
• ISSN: 0263-5577; 1758-5783; 1758-5783
• DOI: 10.1108/IMDS-05-2020-0290

PurposeThis paper investigates the suitability of fuzzy-logic-based support tools for initial screening of manufacturing reshoring decisions.Design/methodology/approachTwo fuzzy-logic-based support tools are developed together with experts from a Swedish manufacturing firm. The first uses a complete rule base and the second a reduced rule base. Sixteen inference settings are used in both of the support tools.FindingsThe findings show that fuzzy-logic-based support tools are suitable for initial screening of manufacturing reshoring decisions. The developed support tools are capable of suggesting whether a reshoring decision should be further evaluated or not, based on six primary competitiveness criteria. In contrast to existing literature this research shows that it does not matter whether a complete or reduced rule base is used when it comes to accuracy. The developed support tools perform similarly with no statistically significant differences. However, since the interpretability is much higher when a reduced rule base is used and it require fewer resources to develop, the second tool is more preferable for initial screening purposes.Research limitations/implicationsThe developed support tools are implemented at a primary-criteria level and to make them more applicable, they should also include the sub-criteria level. The support tools should also be expanded to not only consider competitiveness criteria, but also other criteria related to availability of resources and strategic orientation of the firm. This requires further research with regard to multi-stage architecture and automatic generation of fuzzy rules in the manufacturing reshoring domain.Practical implicationsThe support tools help managers to invest their scarce time on the most promising reshoring projects and to make timely and resilient decisions by taking a holistic perspective on competitiveness. Practitioners are advised to choose the type of support tool based on the available data.Originality/valueThere is a general lack of decision support tools in the manufacturing reshoring domain. This paper addresses the gap by developing fuzzy-logic-based support tools for initial screening of manufacturing reshoring decisions.