A Neuro-Fuzzy Algorithm for Assessment of Macro-Ergonomics and HSE in a Large Petrochemical Plant

Process plants such as petrochemical units have been continuously trying to improve Health, Safety and Environment (HSE) programs. There has been several efficiency frontier analysis methods reported in the literature. However, each of these methodologies has its strength as well as major limitations. This study proposes an adaptive network-based fuzzy inference system (ANFIS) for assessment of HSE programs in a petrochemical plant. The proposed neuro-fuzzy approach is applied to a set of operators in the petrochemical unit to show its applicability and superiority. To achieve the objectives of this study, standard questionnaires with respect to HSE are completed by operators. The average results for each category of HSE are used as inputs and accomplishment of HSE programs is used as output for the algorithm. Moreover, this algorithm is used to rank operators performance with respect to HS. Finally, the algorithm identifies efficient operators with respect to HSE. This is the first study that introduces an intelligence algorithm for assessment and improvement of HSE program in a petrochemical plant

Health Safety, Environment (HSE); Adaptive Network Based Fuzzy Inference System (ANFIS); Human Operators; Performance Assessment; Petrochemical Plants