Artem Tkach

Research Activities

ReMAIntAIn
ndustries with high resource consumption, such as the aluminum continuous casting industry, face major technical and economic challenges. In particular, small-batch production with a wide variety of products, numerous formulations and parameter settings can lead to a multitude of wear phenomena and defects. These causes of defects often cannot be detected by sensors and thus cannot be identified using conventional condition monitoring techniques, which leads to long troubleshooting times. Downtimes thus result in high costs and high energy consumption. As a result, companies usually keep large quantities of spare parts in stock and often replace parts that are still functional early to minimize downtime. However, this results in the waste of valuable resources. Knowledge about past failures and experience with the machine is usually only available to maintenance personnel and is often documented in maintenance and machine logs, but is rarely linked to sensor and process data. Consortium lead: Institute of Industrial Engineering and Management, Industry partner: TU Wien Institute of Management Science, Fried v. Neuman (Aluminium) Gmbh, Mesify Solutions Gmbh

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