Representing energy efficiency diagnosis strategies in cognitive work analysis

Area of Science:

• Cognitive Science
• Human-Computer Interaction
• Energy Management

Background:

• Cognitive Work Analysis (CWA) is a framework for analyzing complex work domains.
• Energy efficiency Monitoring & Targeting (M&T) presents unique challenges for CWA application.
• Existing CWA applications often overlook the nuances of M&T practices.

Purpose of the Study:

• To identify and address theoretical challenges in applying CWA to M&T.
• To explore the utility of Work Domain Analysis (WDA), Control Task (ConTA), and Strategies (StrA) for M&T.
• To inform the design of diagnosis support tools for energy efficiency.

Main Methods:

• Application of Jens Rasmussen's CWA framework.
• Detailed analysis of Work Domain Analysis (WDA), Control Task (ConTA), and Strategies (StrA).
• Modeling solutions developed to overcome identified theoretical issues.

Main Results:

• Eight theoretical issues in applying CWA to M&T were identified and addressed.
• M&T was modeled using two interlinked functions: energy control and knowledge representation maintenance.
• A representation-dependent strategy was identified, highlighting information needs for fault diagnosis.

Conclusions:

• Modified CWA approaches, particularly ConTA and StrA, are valuable for analyzing M&T.
• The findings provide a basis for developing improved diagnosis support tools for energy efficiency.
• Understanding M&T work functions and strategies enhances system performance analysis.