Data-based skill evaluation of human operators in process industry

The operation of industrial process plants is typically supervised by human operators, even though the routine control tasks may be mainly performed by the automation system. When analyzing the efficiency of the plant it is important to consider also the performance of the operators in addition to the automatic control algorithms. In this paper a systematic data-based approach for comparing the skill levels and working methods of process operators is presented. Real process data from a mineral processing plant is used to evaluate and compare how five human operator groups control the same process. The data is clustered and a self-organizing map is used to detect and visualize the operator-specific behaviour and the differences in their skills. It is shown that even though all the operators have at least some experience of the process, their performance varies notably. The final objective of the research is to improve the operation of the process by utilizing the obtained results in training and coaching of the operators.