Optimized Automotive Fault-Diagnosis based on Knowledge Extraction from Web Resources
Simon Meckel, Johannes Zenkert, Christian P. Weber, Roman Obermaisser, Madjid Fathi, Sadat Rubaiyat · 2019
The maintenance and repair of modern vehicles is a challenge for garages, as different causes of faults lead to similar symptoms in the highly complex vehicles these days. Existing processes for fault-diagnosis based on manufacturer service manuals and human experiences are often inadequate and result in high effort and wrong decisions. In addition to these service manuals which provide basic models for e.g., diagnostic terms, primary physical quantities, causal relationships, and plausibilities, nowadays, internet forums offer a comprehensive source of experiences for solutions to these challenges. This paper, therefore, presents methods for the extraction of knowledge from unstructured and informal contributions in internet forums with the goal to synthesize diagnostic graphs from the established knowledge base, which are part of a maintenance software to supports garages in the maintenance of vehicles by suggesting more efficient and target-oriented diagnostic and maintenance actions in real-time.