Design and implementation of a fuzzy expert system for performance assessment of an integrated health, safety, environment (HSE) and ergonomics system: The case of a gas refinery

  • Authors:

  • A. Azadeh;I. M. Fam;M. Khoshnoud;M. Nikafrouz

  • Affiliations:

  • Department of Industrial Engineering, Center of Excellence for Intelligent Based Experimental Mechanics, Department of Engineering Optimization Research, Research Institute of Energy Management an ...;Department of Occupational Health and Safety, Faculty of Health, University of Hamadan Medical Science, Hamadan, Iran;Department of Industrial Engineering, Center of Excellence for Intelligent Based Experimental Mechanics, Department of Engineering Optimization Research, Research Institute of Energy Management an ...;Department of Industrial Engineering, Center of Excellence for Intelligent Based Experimental Mechanics, Department of Engineering Optimization Research, Research Institute of Energy Management an ...

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2008

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Abstract

The objective of this study is to design a fuzzy expert system for performance assessment of health, safety, environment (HSE) and ergonomics system factors in a gas refinery. This will lead to a robust control system for continuous assessment and improvement of HSE and ergonomics performance. The importance of this study stems from the current lack of formal integrated methodologies for interpreting and evaluating performance data for HSE and ergonomics. Three important reasons to use fuzzy expert systems are (1) reduction of human error, (2) creation of expert knowledge and (3) interpretation of large amount of vague data. To achieve the objective of this study, standard indicators and technical tolerances for assessment of HSE and ergonomics factors are identified. Then, data is collected for all indicators and consequently, for each indicator four conditions are defined as ''acceptance'', ''low deviation'', ''mid deviation'' and ''high deviation''. A membership function is defined for each fuzzy condition (set) because an indicator cannot be allocated to just one of the above conditions. The expert system uses fuzzy rules, which are structured with Data Engine. Previous studies have introduced HSE expert system whereas this study introduces an integrated HSE and ergonomics expert system through fuzzy logic.