A unique algorithm for the assessment and improvement of job satisfaction by resilience engineering: Hazardous labs |
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| Affiliation: | 1. School of Industrial Engineering, Center of Excellence for Intelligent-Based Experimental Mechanics, College of Engineering, University of Tehran, Iran;2. Department of Industrial Engineering, Esfarayen University of Technology, Esfarayen 9661998195, Iran;1. College of Civil Engineering, Fuzhou University, Fuzhou 350116, China;2. School of Urban Construction, Yangtze University, Jingzhou 434023, China;1. Rua Senador Pinheiro, 304. Passo Fundo, RS CEP 99070-220, Brazil;2. School of Engineering and Built Environment, Griffith University, 170 Kessels Rd, Nathan, QLD 4111, Australia;3. DEPROT/UFRGS (Industrial Engineering and Transportation Department, Federal University of Rio Grande do Sul), Av. Osvaldo Aranha 99, 5. Andar, CEP 90035-190 Porto Alegre, RS, Brazil;4. UNOCHAPECÓ (Regional University of Chapecó). Rua Barão do Rio Branco, 611-D/101 Chapecó, SC CEP 89801-080, Brazil;1. School of Industrial and Systems Engineering, Center of Excellence for Intelligent-Based Experimental Mechanic, College of Engineering, University of Tehran, Iran;2. Department of Industrial Engineering, Esfarayen University of Technology, Esfarayen 9661998195, Iran;1. School of Industrial and Systems Engineering, Center of Excellence for Intelligent-Based Experimental Mechanic, College of Engineering, University of Tehran, Iran;2. Department of Industrial Engineering, Esfarayen University of Technology, Esfarayen, 9661998195, Iran |
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| Abstract: | There are many potential dangers in laboratories of universities. Hence it should be focused on the actions and decisions of the individuals who work in the labs. Resilience Engineering (RE), the ability to recover quickly after an upset, is known as an important feature of a complex system which handles hazardous technical operations. In response to the need for the betterment of health, safety, and environment (HSE) at work; it is felt necessary to study the RE aspects if an unexpected events occurs. The main purpose of this study is to determine the role and effect of RE in improving job satisfaction and occupational safety in laboratories of universities. This study also presents an intelligent algorithm for assessing and improving job satisfaction in laboratories filled with hazardous materials by means of HSE and RE. In doing so, questionnaires related to HSE and RE are filled in by laboratory operators. The average result of each HSE and RE category is considered as input and job satisfaction as output for the proposed algorithm. An integrated neuro-fuzzy algorithm to find optimal solution is developed and tested for the purpose of this study. Also, results are tested and verified by regression analysis. Finally, with the help of Normal probability technique, outlier laboratories will be identified. The results are improved by means of RE as an input. This is one of the first studies introducing an intelligent algorithm for the improvement of job satisfaction by means of RE and HSE in hazardous laboratories. |
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| Keywords: | Resilience engineering (RE) Health Safety and environment (HSE) Hazardous laboratories Job satisfaction Artificial neural network (ANN) Adaptive network based fuzzy inference system (ANFIS) |
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