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

机译:基于模糊的逻辑的支持工具,用于制造商业重新定义的初始筛选

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Purpose This paper investigates the suitability of fuzzy-logic-based support tools for initial screening of manufacturing reshoring decisions. Design/methodology/approach Two 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. Findings The 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/implications The 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 implications The 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/value There 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.
机译:目的本文调查了模糊逻辑的支持工具,以便初始筛选制造商业的初始筛选。设计/方法/接近两种模糊逻辑的支持工具与瑞典制造公司的专家一起开发。第一个使用完整的规则库和第二个减少的规则库。两个支持工具使用了十六个推理设置。调查结果表明,基于模糊逻辑的支持工具适用于初始筛选制造商品的初始筛选决策。开发的支持工具能够建议是否应根据六个主要竞争力标准进一步评估重置决定。与现有文献相比,本研究表明,在准确性方面是否使用完整或减少的规则基础并不重要。开发的支持工具类似地表现出没有统计学上显着的差异。然而,由于当使用减少的规则基础并且需要更少的资源来开发时,因此更优选用于初始筛选目的时的解释性高得多。研究限制/含义开发的支持工具在主要标准级别实现,并使它们更适用,它们还应包括子标准水平。支持工具也应扩大到不仅考虑竞争力标准,还应考虑与资源可用性和公司的战略定位有关的其他标准。这需要进一步研究了在制造域中的多阶段架构和自动生成模糊规则。实际意义支持工具帮助管理者在最有前途的回顾项目上投入稀缺时间,并通过采取全面的竞争力来实现及时和有弹性的决策。建议从业者根据可用数据选择支持工具类型。原创性/值在制造域中存在普遍缺乏决策支持工具。本文通过开发基于模糊逻辑的支持工具来解决初始筛选制造业重新定义决策的差距。

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