Investigation of performance shaping factors in a practical human-automation interaction system

A safe and secure world needs to effective collaboration between humans and intelligent automation systems, as research on human-automation interaction (HAI) can establish more trust in automation. This paper is intended to investigate the relationship between the human-automation systems and the factors which shape their performance, referred to as performance shaping factors (PSFs). The most influential PSFs are recognized in a practical automation system, and then ranked in order of their influence on HAI performance, by a sensitivity analysis methodology. A subjective approach is employed to explore the experts' judgments; whereas, a reliability analysis ensures the internal consistency of the obtained data. Number of faults per two hours, electric network loading, customer type, service area, age of the plant, and time of day, were respectively found as the most influential PSF; which are reduced to their four superordinate PSFs as task frequency, mental workload, task severity and executability. The paper includes a necessary background on HAI and PSF concepts, research methodology, implementation and results, and a useful context-specific discussion on the results derived from the empirical study.