Toward an Objective Measure of Automation for the Electric Grid

• Published in: Procedia manufacturing 2015, Vol.3, p.5285-5292
• Main Authors: Haass, Michael J., Warrender, Christina E., Burnham, Laurie, Jeffers, Robert F., Stevens-Adams, Susan M., Cole, Kerstan S., Forsythe, Chris
• Format: Article
• Language: English
• Subjects: automation; critical infrastructure; human performance; smart grid
• ISSN: 2351-9789; 2351-9789
• DOI: 10.1016/j.promfg.2015.07.611

The impact of automation on human performance has been studied by human factors researchers for over 35 years. One unresolved facet of this research is measurement of the level of automation across and within engineered systems. Repeatable methods of observing, measuring and documenting the level of automation are critical to the creation and validation of generalized theories of automation's impact on the reliability and resilience of human-in-the-loop systems. Numerous qualitative scales for measuring automation have been proposed. However these methods require subjective assessments based on the researcher's knowledge and experience, or through expert knowledge elicitation involving highly experienced individuals from each work domain. More recently, quantitative scales have been proposed, but have yet to be widely adopted, likely due to the difficulty associated with obtaining a sufficient number of empirical measurements from each system component. Our research suggests the need for a quantitative method that enables rapid measurement of a system's level of automation, is applicable across domains, and can be used by human factors practitioners in field studies or by system engineers as part of their technical planning processes. In this paper we present our research methodology and early research results from studies of electricity grid distribution control rooms. Using a system analysis approach based on quantitative measures of level of automation, we provide an illustrative analysis of select grid modernization efforts. This measure of the level of automation can be displayed as either a static, historical view of the system's automation dynamics (the dynamic interplay between human and automation required to maintain system performance) or it can be incorporated into real-time visualization systems already present in control rooms.