MEET RECOTRANS PARTNER MBT
Mercedes-Benz Türk (MBT), which was established in Istanbul in 1967, is one of the biggest foreign direct investments in Turkey with a total investment volume of € 885 million and employs around 6.000 people. 80% of MBT employees are postgraduates and can speak at least one foreign language. Furthermore 4.000 people are employed in its nationwide dealer and customer service network. Daimler AG currently holds 67% shares in MBT.
Mercedes-Benz Türk produces city-buses and coaches at the Hoşdere Bus Plant in Istanbul and light, medium and heavy duty trucks at the Aksaray Truck Plant. These facilities are an important part of Daimler AG’s development and production network.
MBT R&D Center (Bus & Truck), which is located in Hoşdere Bus Plant, has over 320 employees, more than 80% with a mechanical, electrical, computer engineering or equivalent, including 126 MSc and 5 PhD. The strategy of MBT R&D Center is to service engineering facilities in global development network for specific contents all around the world (Center of Competence), to produce and export technology, to supply the needs of both Turkish and world market, to present industrialised products manufactured in Turkey, to be an active circle of the R&D ecosystem by innovation, innovative technologies and university-industry collaborations. The R&D Department of MBT is specialized in all steps of the development process, from vehicle concept to construction, from simulation calculation to testing. Within new work packages shifting from Germany in scope of Center of Competence (only responsible for all Daimler vehicles in some parts such as propshaft, suspension in truck or route testing, electric diagnose etc.) employee number is increasing. MBT designing its future is on six main topics: Connectivity, autonomous driving, mobility, electrifications, safety and efficiency (reducing the cost and emissions, increasing efficient use of energy and resources).


» Author: AIMPLAS
» Publication Date: 28/09/2018
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement Nº 768737