4.7 Article

A conflict elimination-based model for failure mode and effect analysis: A case application in medical waste management system

Journal

COMPUTERS & INDUSTRIAL ENGINEERING
Volume 178, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2023.109145

Keywords

Failure mode and effect analysis; Social network analysis; Conflict elimination; Medical waste management; Evidence theory; DEMATEL-TODIM

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This study constructs a FMEA model with internal and external team members for medical waste management system and focuses on conflict elimination under social network to improve team harmony and enhance the reliability of FMEA.
As a recognized and powerful risk analysis tool, failure mode and effects analysis (FMEA) has proven its effectiveness in medical waste management, which has profound significance to human health and ecological environment. However, existing FMEA studies pay little attention to the heterogeneity of team members (TMs) and their trust relationship, potentially leading to inappropriate results. Therefore, this paper constructs a FMEA model with internal and external TMs for medical waste management system, which focuses on the conflict elimination under social network to circumvent TMs' negative behaviors and improve team harmony, thereby enhancing the reliability of FMEA. Firstly, to increase the flexibility and accuracy of information expression and synthesis, probabilistic linguistic term sets (PLTSs) and Dempster-Shafer evidence theory (D-S theory) are employed to provide and process evaluations of failure modes (FMs). Secondly, an objective trust prediction method based on bounded confidence is proposed for building a credible social network. Thirdly, a conflict elimination mechanism is devised to improve team cohesion, in which TM weights are dynamically determined. Afterwards, an integrated DEMATEL-TODIM decision framework is proposed to prioritize FMs. An application and related analysis prove that the proposed model can effectively improve the social relationship of TMs and obtain a reliable ranking of FMs on the basis of discriminating FMs' causality while considering TMs' bounded rationality.

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