The ForTune Toolbox: Building Solutions for Condition-Based and Predictive Maintenance Focusing on Retrofitting
Konferenz: MikroSystemTechnik Kongress 2023 - Kongress
23.10.2023-25.10.2023 in Dresden, Deutschland
Tagungsband: MikroSystemTechnik Kongress 2023
Seiten: 6Sprache: EnglischTyp: PDF
Autoren:
Assafo, Maryam (Department of Wireless Systems, BTU Cottbus-Senftenberg, Cottbus, Germany)
Lautsch, Martin (Department of Automation Technology, BTU Cottbus-Senftenberg, Cottbus, Germany)
Suawa, Priscile; Huebner, Michael; Reichenbach, Marc (Department of Computer Engineering, BTU Cottbus-Senftenberg, Cottbus, Germany)
Jongmanns, Marcel (Fraunhofer IPMS, Dresden, Germany)
Brockmann, Carsten; Reinhardt, Denis (IZM, Berlin, Germany)
Langendoerfer, Peter (Department of Wireless Systems, BTU Cottbus-Senftenberg, Cottbus, Germany & IHP—Leibniz-Institut für innovative Mikroelektronik, Frankfurt/Oder, Germany)
Inhalt:
Condition-based and predictive maintenance (PdM) will play a pivotal role in improving sustainability. This holds true not only for production systems but also for other machinery, e.g., trains, construction machines, etc. A common feature of these systems is that they are in use for long terms, often several decades. Thus, in order to use an innovative approach such as an artificial intelligence-based maintenance optimization, appropriate means to select, deploy, and evaluate the data for these systems are essentially needed. Empowering retrofitting is what the ForTune Toolbox aims for by providing the hardware and software needed to enable the deployment of PdM solutions. In this paper, we present the concept of the toolbox.