A Human Factors Approach to Supervisory Control Interface Improvement

In recent years, control systems and the role of control room human operators have changed dramatically. Human operator activity has evolved from manually performing the process, to control system supervision. Today, the human operator requires an in-depth knowledge of the process that he/she is overseeing and the ability to make effective decisions within demanding constraints. The increased complexity of industrial process control calls for a new methodological approach (for research and design purposes), which reproduces the essential components of current control systems: the environment, the task at hand and human operator activity (Samad & Weyrauch, 2000). The complexity of industrial process supervision makes it necessary to supplement the Control Engineering approach with a cross-disciplinary cooperation in order to integrate knowledge and methods from other fields, especially Human Factors, Human-Computer Interaction and Artificial Intelligence (Granollers et. al., 2005), (Holstom, 2000), (Petersen, 2000). Our view is that complete control systems engineering must encompass all these approaches. Human Factors is concerned with the adaptation of technology to suit human operator need and ability so as to achieve effectiveness, efficiency and user/worker satisfaction and comfort (Wickens et. al., 1997). In the domain of human factors in control room design the aim is to help engineers to design better systems and processes, increase operational safety and efficiency (Noyes & Bransby, 2001). One of the main references in telerobotics, automation and human supervisory control is Thomas B. Sheridan, who had an influence on professionals of the areas of engineering of systems and human factors along two decades (Sheridan, 1992). One of this author's main ideas is that the progresses in robotics do not only depend on the changes in the technology, but also on the advances in the understanding of the relationship between humans and machines. One example is the development of human interaction for multiple robotic systems that incorporate intelligent decision support capabilities via distributed artificial intelligence (Adams, 2006). O pe n A cc es s D at ab as e w w w .ite ch on lin e. co m