Identifying Problems and Generating Recommendations for Enhancing Complex Systems: Applying the Abstraction Hierarchy Framework as an Analytical Tool

Abstract

Objective: This study adopts J. Rasmussen's (1985) abstraction hierarchy (AH) framework as an analytical tool to identify problems and pinpoint opportunities to enhance complex systems. Background: The process of identifying problems and generating recommendations for complex systems using conventional methods is usually conducted based on incompletely defined work requirements. As the complexity of systems rises, the sheer mass of data generated from these methods becomes unwieldy to manage in a coherent, systematic form for analysis. There is little known work on adopting a broader perspective to fill these gaps. Method: AH was used to analyze an aircraft-automation system in order to further identify breakdowns in pilot-automation interactions. Four steps follow: developing an AH model for the system, mapping the data generated by various methods onto the AH, identifying problems based on the mapped data, and presenting recommendations. Results: The breakdowns lay primarily with automation operations that were more goal directed. Identified root causes include incomplete knowledge content and ineffective knowledge structure in pilots' mental models, lack of effective higher-order functional domain information displayed in the interface, and lack of sufficient automation procedures for pilots to effectively cope with unfamiliar situations. Conclusion: The AH is a valuable analytical tool to systematically identify problems and suggest opportunities for enhancing complex systems. It helps further examine the automation awareness problems and identify improvement areas from a work domain perspective. Application: Applications include the identification of problems and generation of recommendations for complex systems as well as specific recommendations regarding pilot training, flight deck interfaces, and automation procedures.