Empowering Industrial Maintenance Personnel with Situationally Relevant Information using Semantics and Context Reasoning

Industrial maintenance is a complex discipline requiring experience and know-how. Information such as maintenance work orders are usually provided through mobile devices to field personnel. There are also other information sources with manuals, documented history, contact information etc. that is of value supporting the tasks at hand but typically this needs to be retrieved manually. The challenge is how to utilize information originating from heterogeneous information sources that, in addition, may change e.g. for outsourced maintenance service providers taking care of different sites. To facilitate the use of supporting materials an ontology knowledge management approach is developed that integrates data and documents, and provides relevant information for the task at hand using context and semantics based reasoning. Results from early prototyping show that the approach can improve utilization of information in existing systems through adapter layers and complement existing mobile a s well as upcoming augmented reality applications by automatically providing situationally relevant information.