Rieger Metallveredlung GmbH & Co KG received the TOP 100 award on June 27. The science journalist Ranga Yogeshwar accompanied the innovation competition, which was held for the 32nd time, as a mentor. Rieger Metallveredlung took part in the competition in size category A (up to 50 employees in Germany) and was honored in the categories external orientation / open innovation and innovation-promoting top management. This is the second time that the company has been one of the top innovators.
Aluminum - that's what we love
The company portrait published on the occasion of the award states: "Aluminum - that's what we love." Franz Rieger, owner and Managing Director of Rieger Metallveredlung GmbH & Co KG, knows why: "It is the metal of choice for lightweight construction, but it is not easy to refine. The medium-sized company therefore invests six-figure sums in research every year to improve material properties and surface appearance. In the search for optimization potential, the management also keeps an eye on energy consumption and CO₂ emissions.
Heat pump for the administration
Last year, Rieger managed to generate a fifth more turnover while simultaneously reducing energy consumption. Reducing energy consumption and CO₂ emissions is a high priority for the management. In recent months, Franz Rieger has had a heat pump installed in the administration department. There are also plans to use electric cars as company vehicles and to equip the company with e-scooters.
Tin-plated aluminum for e-cars
Rieger generates half of its turnover with the automotive industry. The tinning of aluminum plays a particularly important role in e-mobility. Battery packs with parts refined by Rieger are installed by numerous manufacturers. Refined aluminum parts are also used in decentralized power supplies. Cable connectors hold the cables of the expanded networks together. Together with research institutes, Rieger optimizes the material properties of aluminium for these applications. The finishing processes themselves are also examined for their optimization potential.