Yanni Apers

(EN) Predictive maintenance based on machine data – optimizing process efficiency using the metal industry as an example

In this podcast episode, we dive into the day-to-day job of someone in charge of production. This person must meet production goals, as well as schedule maintenance downtime in coordination with production planning. One of the world’s largest copper recyclers – Aurubis AG – explains the challenges and strategic objectives of digitization today. One of the leading suppliers of non-ferrous metals is supported by its partner azeti, which enables fast and scalable solutions for the implementation of Internet-of-Things projects. Together, they will present their flagship IoT project, which revolves around the copper smelting furnace, the electric inductor. This inductor and the associated production equipment must run 24/7 over a long period of time. Planning production shutdowns is not always easy – especially when unforeseen production downtime occurs. This podcast episode shows how azeti helps their customer Aurubis in this point and realizes the condition monitoring of the inductor. This includes, for example, the monitoring of electrical parameters, process temperatures and pressures. azeti’s goal: to achieve a higher level of transparency, cost efficiency, resilience and sustainability in production for its customers. Madeleine Mickeleit’s guests on this podcast episode: Florian Hönigschmid (Vice President Strategy & Sales, azeti) Yanni Apers (Production Manager Aurubis Olen)