A novel intuitionistic fuzzy FMEA framework with Dombi aggregation for service quality in industry 4.0: application in higher education
Abstract
Higher educational service quality (HSQ) is one of the prominent areas redefined in I4, imposing many challenges on higher educational institutions (HEIs). In this context, the present work aims to fulfill two objectives: a) to develop a novel risk assessment framework for failure mode and effect analysis (FMEA) using intuitionistic fuzzy set (IFS); b) to assess potential risk factors or failures faced by HEIs in delivering superior HSQ in Industry 4.0 (I4). The present work uses a multi-criteria decision-making (MCDM) model, such as comparisons between ranked criteria (COBRAC), with IFS-based Dombi aggregation for group decision-making, to develop a novel extension of the FMEA framework. The present work proposes an innovative approach by incorporating an additional dimension in the classical FMEA model, such as intractability. The failure modes (FM) are identified from the viewpoint of HSQ attributes. Subsequently, the present work examines the validity of the outcome by comparing several MCDM models and sensitivity analysis. Based on the opinions of 23 experts, the current work reveals the dominance of risk factors, such as ethical concerns (FM-9), infrastructural constraints (FM-2), and shortage of funds (FM-6). The ongoing study provides several novelties, such as an extension of FMEA with an additional dimension and IFS-Dombi aggregation, using the COBRAC model for FMEA, and an innovative approach to risk assessment for HSQ, which are helpful for decision-makers and researchers.
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