Join this workshop where you will have the opportunity to hear the presentations below.

Three pillars of modern condition monitoring
In this presentation, we will introduce you to the three essential components of modern condition monitoring projects. From precise and fail-safe data acquisition through synchronization and joint analysis of decentrally acquired data to the point of worldwide location-independent visualization, we explain what is important in modern condition monitoring projects. Presenting various case studies, we illustrate how these requirements can be successfully implemented in different application areas.

Case Study: Instrumentation of a prototype E-Motor
Takeaways
▪ Multiple ways to detect a failure (temp, vib, position, supply current etc.)

Data-driven analysis: Example of big data approaches for analyzing measurement data
Takeaways
▪ To go into production – how to transform PoC’s into companywide productive environments

Case Study: Advanced bearing fault detection (algorithm development)
Takeaways
▪ Test design & validation criteria for failure detection algorithms – Controlled environment for validation – Online / instationary “real life” application
▪ Approach on the development of a signal conditioning and online fault failure detection

Dr. Sven Jodlauk graduated in physics from the University of Cologne and subsequently obtained his PhD in the field of multiferroic materials. He then worked for several years as head of the testing technology department in a rail rolling mill. There, various physical measuring methods were used to monitor the quality of the rails produced.

In his current position as product manager at Delphin Technology AG, he is responsible for identifying current market and customer requirements in the field of measurement technology and translating them into precisely tailored products and complete solutions. Condition monitoring is a major application focus at Delphin Technology AG.

Dipl. Ing. Hannes Gruber is a Lead Engineer at AVL List GmbH in Graz, responsible for the mechanical design of complex testbed solutions in the fields of motor racing and hybrid technologies. He holds a Dipl.-Ing. (MSc) and a BSc in Mechanical Engineering from the Technical University of Graz (2019 & 2016). In 2011 he started his professional career at AVL List Gmbh in Graz in the racing department as a student trainee. From 2013 till 2017, he was appointed the role Solution Engineer, developing testbed concepts in the field of racing. Since 2017, in his role as a Lead Engineer, he is leading several research projects related to his areas of expertise. During his professional life, he filed several patents.

Gerhard Schagerl received his MSc in 2003 in computer science at the Johannes Kepler University Linz, Austria. Gerhard is employed at AVL List GmbH since 2000. From 2018 Gerhard joined AVL’s Big Data efforts in the role as Product Manager for Big Data and AI services. In this position he defines strategy and product portfolios, but also develops new data-driven business models. Recently AVL’s service portfolio was extended to the Product Line for Data Intelligence which is now in Gerhard’s responsibility.

László Baló MSc is a Data Scientist at AVL List GmbH in Graz working closely with stakeholders throughout the organization of AVL to identify opportunities using data and knowledge from the automotive domain to drive business solution. In his most recent projects, the focus is on building POCs by applying machine learning methods and deploying the resulting applications companywide on-prem or in the cloud.