Augmented Reality for Machine Maintenance Applications

Nowadays, organizations have to cope with different challenges, such as varying factors concerning the requirements of the markets, products, and services. Therefore, organizations have to constantly improve their business processes to keep up with these varying demands. For instance, the maintenance processes of a machinery and physical systems may have many different procedures depending on external process factors (such as customer requirements and specifications) and internal factors (i.e., utilized machines, machine types, attrition of machine parts, knowledge level of a maintenance operator). Ultimately, used process management concepts and systems have to support variability and context data management during modeling and execution time.

This thesis develops a context- and process-aware information system to support maintenance operators with their daily work tasks. Thereby, augmented reality is used for interaction between a maintenance operator and the developed proof-of-concept implementation. The latter acquires sensor data from different information systems, executes and adapts executed process based on the current contextual situation, and visualizes augmented guidelines to maintenance operators in real time. By using such a context-aware process information system during a maintenance routine, organizations are able to improve quality and time efficiency of a maintenance routine.