A hybrid decision-making technique based on extended entropy and trapezoidal fuzzy rough number

Abstract

The fourth industrial revolution, in which mechanical appliances can be precisely and automatically handled, depends extensively on intelligent manufacturing. It has the potential to create more productive manufacturing facilities. Still, defects and possible mishaps in the production process affect the workflow, deplete resources, and worsen environmental effects. Failure modes and effects analysis (FMEA) is a systematic method for identifying, analyzing, and removing possible failures in products, designs, and procedures. Due to uncertainty’s multiple nature, more than one method or technique is needed to deal with such flaws or failures. Ultimately, there is a dire need to develop hybrid models to address and resolve manufacturing process failures. Many fuzzy rough MCDM techniques have been designed to deal with and quantify uncertainty when assessing failure modes; these methods often use triangular fuzzy numbers and FMEA. When modeling complex and asymmetric fuzzy sets, trapezoidal fuzzy numbers offer a more expressive and accurate alternative to the more basic and limited triangle fuzzy numbers. This study proposes a novel approach to prioritize FMEA risks by combining trapezoidal fuzzy rough numbers with VIKOR method to address ambiguity in expert opinions. Using fuzzy rough intervals rather than a single crisp value, fuzzy rough numbers are utilized to deal with ambiguous information regarding linguistic variables. Robots employed in the cabal industry can have their potential failures identified and assessed more effectively with the help of the suggested trapezoidal fuzzy rough FMEA technique.