Abstract
Researchers have been continuously trying to improve human performance with respect to Health, Safety and Environment (HSE) and ergonomics (hence HSEE). Performance measurement and assessment of operators are fundamental to management planning and control activities, and accordingly, have received considerable attention by both management practitioners and theorists. 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 a non-parametric efficiency frontier analysis methods based on Adaptive Network-Based Fuzzy Inference System (ANFIS) for measuring efficiency as a complementary tool for performance assessment and improvement of operators. The proposed ANFIS algorithm is able to find a stochastic frontier based on a set of input-output observational data and do not require explicit assumptions about the functional structure of the stochastic frontier. Furthermore, it uses a similar approach to econometric methods for calculating the efficiency scores. The proposed approach is applied to a set of operators in a petrochemical unit to show its applicability and superiority. In fact, this study proposes an adaptive intelligence algorithm for measuring and improving job security among operators with respect to HSE-Ergonomics in a petrochemical unit. To achieve the objectives of this study, standard questionnaires with respect to HSE-Ergonomics are completed by operators. The average results for each category of HSE-Ergonomics are used as inputs and work job security is used as output for the algorithm. Moreover, this algorithm is used to rank operators performance with respect to HSE-Ergonomics. Finally, normal probability technique is used to identify outlier operators. This is the first study that introduces an integrated intelligence algorithm for assessment and improvement of human performance with respect to HSE-Ergonomics program in complex systems.
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