Selecting optimal honeycomb structural materials for electronics clean rooms using a Bayesian best-worst method and ELECTRE III

Abstract

In recent years, semiconductors have become essential components in a wide range of electronic information products. The manufacturing of semiconductors requires production in an electronic clean room. Choosing the right honeycomb structural material (HSM) can maximize the efficiency and operation of the electronic clean room. Nonetheless, selecting the optimal HSM for electronics clean rooms requires balancing tradeoffs between conflicting criteria. This study aims to develop a comprehensive evaluation criteria system for proper HSM selection. We propose a multi-criteria decision support framework based on the notion of basic uncertain linguistic information and an integrated approach that combines the Bayesian best-worst method technique with the Elimination Et Choix Traduisant la Realité (ELECTRE) III method. The proposed framework is used to address the HSM selection problem faced by a cross-functional team who are responsible for the design and construction of an electronics clean room. The results of the case study show that construction cost and clean ventilation capacity criteria are very important and that Sheet Molding Compound straight cylinders, a subtype of HSM, stand out from the crowd of materials. The proposed model was further subjected to sensitivity and comparative analyses to compare the current model with several existing methods to validate its advantages and confirm its validity.