Developing a Fuzzy TOPSIS Model Combining MACBETH and Fuzzy Shannon Entropy to Select a Gamification App

An Integrated Fuzzy DEMATEL and Fuzzy TOPSIS Method for Analyzing Smart Manufacturing Technologies

I4.0 promotes a future in which highly individualized goods are mass produced at a competitive price through autonomous, responsive manufacturing. In order to attain market competitiveness, organizations require proper integration of I4.0 technologies and manufacturing strategy outputs (MSOs). Implementing such a comprehensive integration relies on carefully selecting I4.0 technologies to meet industrial requirements. There is little clarity on the impact of I4.0 technologies on MSOs, and the literature provides little attention to this topic. This research investigates the influence of I4.0 technologies on MSOs by combining reliable MCDM methods. This research uses a combination of fuzzy DEMATEL and fuzzy TOPSIS to evaluate the impact of I4.0 technologies on MSOs. The fuzzy theory is implemented in DEMATEL and TOPSIS to deal with the uncertainty and vagueness of human judgment. The FDEMATEL was utilized to identify interrelationships and determine criterion a’s weights, while the fuzzy TOPSIS approach was employed to rank the I4.0 technologies. According to the study’s findings, cost is the most critical factor determining MSOs’ market competitiveness, followed by flexibility and performance. On the other hand, additive manufacturing (AM) is the best I4.0 technology for competing in the global market. The results present an evaluation model for analyzing the relative important weight of multiple factors on MSOs. They can also assist managers in concentrating on the most influential factors and selecting the proper I4.0 Technology to preserve competitiveness.

Fuzzy-MACBETH Hybrid Method: Mathematical Treatment of a Qualitative Scale Using the Fuzzy Theory

This paper describes the research procedures adopted in developing a triangular fuzzy number scale based on the semantic scale of MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique). The objective was to mathematically treat the uncertainty and subjectivity of linguistic variables used to assess a decision problem. A matrix was initially obtained based on a decision maker’s assessment of a given context analysis. This decision matrix was then fuzzified based on a triangular Fuzzy numbers scale. Next, the inference process was performed using F-LP-MACBETH linear programming problem proposed here, resulting in a Fuzzy scale. This scale was then defuzzified using the centroid method, from which a crisp basic scale emerged, which was then cardinalized. The results show that the MACBETH Fuzzy method proposed here can overcome the classical method’s cardinal inconsistency problem, which facilitates its application in complex contexts. Hence, the MACBETH Fuzzy Hybrid method generated numerical values based on the decision makers’ semantically consistent assessments in a decision matrix, which by the classical method presents cardinal inconsistency. Therefore, the advantage of the proposed method consists in the possibility of obtaining a cardinal scale aligned to the decision makers’ preferences without the need to reassess the context.