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

Per Hilletofth,Movin Sequeira,Wendy Tate

doi:10.1108/imds-05-2020-0290

Abstract

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.

Highlights

Over the last three decades an extensive movement of manufacturing activities from high-cost to low-cost contexts has taken place (Brennan et al, 2015; Ketokivi et al, 2017)
The aim of this research is to investigate the suitability of fuzzy-logic-based support tools 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

Summary

Introduction

Over the last three decades an extensive movement of manufacturing activities from high-cost to low-cost contexts has taken place (Brennan et al, 2015; Ketokivi et al, 2017). This offshoring has been sustained by the idea that there is a compelling advantage in having manufacturing located in low-cost environments. The decision-making frameworks that were used and the calculations generated were rudimentary (Bailey and De Propris, 2014; Stentoft et al, 2015) Another reason that offshoring decisions over time have become less attractive is that the market has evolved, favoring other types of supply chain designs (Hilletofth et al, 2019a). These offshoring failures and market changes have led to an intensified debate about the opposing movement of material and services (reshoring), back to the home country (Arlbjørn and Mikkelsen, 2014; Gray et al, 2013), or to an adjacent country (Panova and Hilletofth, 2017)

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Discussion

Conclusion