Optimizing human-system interface automation design based on a skill-rule-knowledge framework

This study considers the technological change that has occurred in complex systems within the past 30 years. The role of human operators in controlling and interacting with complex systems following the technological change was also investigated. Modernization of instrumentation and control systems and components leads to a new issue of human-automation interaction, in which human operational performance must be considered in automated systems. The human-automation interaction can differ in its types and levels. A system design issue is usually realized: given these technical capabilities, which system functions should be automated and to what extent? A good automation design can be achieved by making an appropriate human-automation function allocation. To our knowledge, only a few studies have been published on how to achieve appropriate automation design with a systematic procedure. Further, there is a surprising lack of information on examining and validating the influences of levels of automation (LOAs) on instrumentation and control systems in the advanced control room (ACR). The study we present in this paper proposed a systematic framework to help in making an appropriate decision towards types of automation (TOA) and LOAs based on a 'Skill-Rule-Knowledge' (SRK) model. From the evaluating results, it was shown that the use of either automatic mode or semiautomatic mode is insufficient to prevent human errors. For preventing the occurrences of human errors and ensuring the safety in ACR, the proposed framework can be valuable for making decisions in human-automation allocation.