Toward an understanding of DCS control operator workload

Abstract

The relatively new technology of distributed control (DCS) has created a long list of new problems that must be solved and questions that must be answered. One perplexing question encountered by control system engineers is how to gauge DCS control operator workload and, more importantly, how to discern if the operator's workload is excessive. The introductions of local control networks and advanced control require more sophisticated metrics of workload than simply counting control loops and using the 200 control loops per operator rule of thumb. Studies have also shown that there is little correlation between the number of control loops and many parameters used to gauge operator workload (such as control moves per hour). This paper will investigate current issues of DCS control operator workload in three main topic areas. First, the paper will briefly define factors that contribute to control operator workload and introduce a model of control operator workload. Control operator workload is a multifaceted construct affected by a host of interacting variables including the operator/control system interface (display and alarm system design), process dynamics, operator training/experience, and crew interaction. Next, the paper will briefly describe strategies that can be used to assess operator workload. Techniques used to assess workload are traditionally divided into three categories: (1) Subjective measures (NASA-TLX, developed by NASA, and SWAT, developed by the U.S. Air Force); (2) Physiological measures (heart rate and eye blink rate); and (3) Performance based measures (such as the number of control moves or alarms per hour, or where performance is measured on a secondary task that the operator completes). Also, the paper will discuss which are the easiest and most appropriate techniques to use with control operators. Finally, the paper will present a workload study of a petrochemical plant DCS control operator job. The study represents a typical control operator loading and how the workload ratings change in response to increasing job demands. The paper will define performance based parameters which are indicative of excessive workload. Also, the paper will touch on the effects of advanced control on operator workload and will discuss stategies that the control system designer can use to reduce workload.