Justification for the selection of manufacturing technologies: a fuzzy-decision-tree-based approach

Abstract

In this paper, a developed model for the justification of alternative manufacturing technologies is presented. The approach, based on fuzzy decision trees, provides a methodology capable of identifying patterns within a technology case repository to support the evaluation of manufacturing systems. Experts are highly influential individuals in the decision process; they provide support and guidance when selecting investments. The experience-oriented task is founded on previous cases or an experts’ experience, and therefore difficult to express in a rational form. The concept is based on a number of characteristics of the case-based reasoning, rule induction and expert system theory. Structured around the fuzzy-decision-tree data-mining technique, the framework provides the ability of using regulated case information to act as structured experience for assisting in the decision process. Fuzzy induction extracts formal rules from a set of experience data, and the expert system philosophy computes the experience base of human expertise for problem-solving. A test case indicates the stability of the classification algorithm and verifies the applicability within the domain.