Call: R&D program "Information and communication technology"
Project management: Prof. Dr. Christian Janiesch
Project participants: APE Engineering GmbH, Möhringer Anlagenbau GmbH, Julius-Maximilians-Universität Würzburg, Friedrich-Alexander-Universität Erlangen-Nürnberg
Project start : 01.01.2018
Project end: 31.12.2019
Funding volume: 500,000 Euro
Funding source: Bayerisches Staatsministerium für Wirtschaft, Landesentwicklung und Energie (StMWi)
A raging stream of state data is the byproduct of modern industrial plants in the Digital Factory. This data stream drives digital industrial service systems that are based on real-time data evaluation. For example, researchers and developers in companies and at universities have developed numerous methods and techniques for the predictive maintenance of plants. For the classic industrial task area of technical documentation, which is increasingly challenged and in some cases overwhelmed by the complexity of modern industrial plants, the innovation potential of digitization has not yet been tapped in a structured way. AutoCoP is based on the conviction that the data infrastructure of the digital factory and intelligent algorithms can structure and dynamically rewrite plant documentation in a (partially) automated manner. By evaluating sensor data, AutoCoP detects anomalous behavior and fault cases of industrial plants and merges these observations with contextual information as well as expert knowledge of experienced editors. This results in clear action instructions for complex fault cases, which are provided at the machine and enable diagnoses as well as corrections by users with different experience and qualifications.