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University laboratories involve various occupational hazards during the research and course activities, which might affect health and safety of both researchers and students, including chemical, physical, electrical, mechanical, as well as ergonomic and psychosocial risk factors. There are many aspects open to improvements in Occupational Health and Safety management of laboratories, and it is required to deal with risks, reduce them in an acceptable level, and implement control measures. In this study, a risk assessment approach is proposed for the university laboratory operations. The proposed approach incorporates 5S methodology, failure modes and effects analysis (FMEA), interval type-two fuzzy sets (IT2FSs), analytic hierarchy process (AHP), and the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). AHP is injected into IT2FSs in the phase of evaluation and weighting of severity (S), occurrence (O), and detectability (D) parameters of FMEA. By applying IT2FVIKOR, it is aimed at prioritizing the emerged hazards in the chemical laboratory of the observed university. The proposed approach reveals the important hazards and suggests control measures for managing them. The study methodologically contributes to risk assessment in the knowledge, while a case study in a chemical laboratory of a newly established university offers an insight into education industry in safety improvement. [ABSTRACT FROM PUBLISHER]

This study proposes an improved failure mode and effect analysis (FMEA) with fuzzy Bayesian Network (FBN) and fuzzy best-worst method (FBWM) to assess failures in plastic production. To eliminate the drawbacks of the classical risk priority number (RPN) computation of FMEA, this approach is developed. Unlike classical RPN, a new parameter hierarchy is constructed, and three sub-parameters are injected into the approach. These parameters are weighted by the aid of FBWM. Hereafter, a fuzzy rule-based system is constructed by incorporating Bayesian Network (BN). Also, a sensitivity analysis is performed to observe the final FMEA score changes in accordance with the change of subjective probability values. Finally, a comparative analysis with two approaches of classical FMEA and FBWM-based FMEA (without a fuzzy rule-based system incorporating BN) is fulfilled. The results of the study are strengthened with the experts' opinions regarding the importance of failure modes for the final product and the whole system and supported them by experience feedback in the observed facility. • A manufacturing failure mode and effect analysis (FMEA) is proposed. • The proposed FMEA is based on fuzzy and probabilistic risk assessment. • Bayesian network (BN) and Best-Worst method (BWM) are used under fuzzy concept. • A case study for plastic manufacturing is performed for demonstration. • A sensitivity and comparative analysis is performed for the validation of results. [ABSTRACT FROM AUTHOR]