Improved remote prediction and collaborative identification of machine defects to reduce downtimes

Technological innovations as described in result #1 and result #2 provide new approaches for simplified remote access and data harmonization among distributed resources which allows new ways to deal with predictive and remote maintenance. Using the ComVantage approach, analysis and diagnosis of machines is possible independent from the location of the machines and service personnel. The technical foundation of the ComVantage approach offers uniform access to heterogeneous data sources based on Linked Data-driven harmonization and interlinking of data sets across organizational boundaries. Therefore a large number of data of similar machines (differences may result, for instance, from different service patches) can be collected and used as a basis for defining analysis algorithms for subsequent corrections. Automated execution of these algorithms provides comprehensive monitoring capabilities and improves the quality and preciseness of error prediction. By harmonizing and interlinking these technical machine data with organizational data of the company, the effort for maintenance is further reduced by coordinating and optimizing analysis and diagnosis plus avoiding duplicate analysis by different employees. Any technician involved with repair actions of some machine is able to see immediately, which tests had already been performed by other technicians for this machine and can use the existing results for the diagnosis. ComVantage furthermore enables the execution of interorganizational workflows that facilitates the collaboration of remote experts (refer to result #6 for details). Onsite service technicians can request live support from remote experts that uses the remote access and analytic capabilities offered by ComVantage and the Mobile Maintenance-oriented application stack. According to our business simulations, maintenance service efficiency and quality is significantly increased (e.g. ~10% decrease on mean-time-to-repair) while operational costs (e.g. utilization and travel of experts) are reduced.