Roxane Koitz, Johannes Lüftenegger, Franz Wotawa
Koitz R., Lüftenegger J., Wotawa F. (2017) Model-Based Diagnosis in Practice: Interaction Design of an Integrated Diagnosis Application for Industrial Wind Turbines. In: Benferhat S., Tabia K., Ali M. (eds) Advances in Artificial Intelligence: From Theory to Practice. IEA/AIE 2017. Lecture Notes in Computer Science, vol 10350. Springer, Cham
Publication year: 2017

Model-based diagnosis derives explanations for discrepancies between the expected and observed system behavior by relying on a formal representation of the artifact under consideration. Although its theoretical background has been established decades ago and various research prototypes have been implemented, industrial applications are sparse. This paper emphasizes the role of essential technology acceptance factors, i.e., usefulness and usability, within the context of model-based diagnosis. In particular, we develop a concept and interface design for an abductive model-based diagnosis application integrated into existing condition monitoring software for industrial wind turbines. This fault identification tool should enhance the performance of the maintenance personnel while respecting their current work processes, taking into account their particular needs, and being easy to use under the given work conditions. By employing an iterative design process, continuous feedback in regard to the users’ work goals, tasks, and patterns can be included, while also considering other stakeholders’ requirements. The result is a workflow and interface design proposal to be implemented in the final software product.