The development of modern automated production systems requires the close cooperation of engineers from different domains. Due to the large amount of domain-specific documents and heterogeneous data they create during the multidisciplinary engineering activities, ensuring the consistency of information is always challenging. Since most of these documents are texted-based and lack a standardized structure, extracting required information from these files is oftentimes problematic. This issue is particularly critical in the development of large-scale production plants due to the high complexity of the systems and the diversity of disciplines involved. To help engineers efficiently utilize unstructured data sources as well as identify potential information contradictions, we propose an ontology-based inconsistency management approach for large-scale production systems that generates the knowledge base from unstructured engineering data and (semi-) automatically detects multiple types of inconsistencies. In addition, the presented framework also supports the tracking of information changes during the system design process.     «

The development of modern automated production systems requires the close cooperation of engineers from different domains. Due to the large amount of domain-specific documents and heterogeneous data they create during the multidisciplinary engineering activities, ensuring the consistency of information is always challenging. Since most of these documents are texted-based and lack a standardized structure, extracting required information from these files is oftentimes problematic. This issue is p...     »