Automatic generation of fuzzy inference rules in a reshoring decision context

• This paper presents a decision-support system for reshoring decision-making based on fuzzy logic. The construction and functionality of the decision-support system is briefly outlined and evaluated in a highcost environment contemplating six specific decision criteria, namely cost, quality, time, flexibility, innovation and sustainability. A major challenge with fuzzy logic solutions has to do with the construction of the fuzzy inference rules. In the relocation domain, the fuzzy inference rules represent the knowledge and competence of relocation experts and they are usually created manually by the same experts. One obstacle is that the complexity of the fuzzy inference rules increases with the number of decision criteria. To overcome this complexity issue, this paper presents a solution whereby the fuzzy inference rules are automatically generated by applying one hundred reshoring scenarios as input data. The reshoring decision recommendations produced by the fuzzy logic decision-support system are demonstrated to be close to those of human reshoring domain experts.

Ämnesord

SAMHÄLLSVETENSKAP  -- Ekonomi och näringsliv (hsv//swe)

SOCIAL SCIENCES  -- Economics and Business (hsv//eng)

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Produktionsteknik, arbetsvetenskap och ergonomi (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Production Engineering, Human Work Science and Ergonomics (hsv//eng)

Nyckelord

decision-support system

fuzzy inference rule generation

fuzzy logic inference system

membership function generation

reshoring.

Production Engineering

Human Work Science and Ergonomics

Produktionsteknik

arbetsvetenskap och ergonomi

Publikations- och innehållstyp

ref (ämneskategori)

kon (ämneskategori)