Understanding Perceived Complexity in Human Supervisory Control

Abstract

Industrial processes are becoming more complex owing to technological developments and new opportunities. Technological developments, hardware and software, have become more reliable and system configurations more robust. However, the reliability of operator control actions has not improved at the same pace. Consequently human reliability has become the relatively weakest aspect of automated, operator-supervised systems. Hence, understanding how the human operator experiences increasing complexity may play an important role in task allocation and human–machine system design. In this paper the perceived complexity is studied within four typical operational environments in supervisory control. Mathematical formulations for these four operational environments are proposed, and their properties are analysed. A laboratory system is used to investigate the perceived complexity under various operational environments. The experimental results show a significantly different perceived complexity for the coupled and uncoupled operation environments. Extrapolation of the results revealed that the operator would have perceived the system as extremely complex if he/she would have to operate more than eight strongly interconnected subsystems extensively in 30 minutes. Implications of this study are also addressed.