As part of its plans to invest $1.3 billion to expand SUV production at its Tuscaloosa plant in the US, Mercedes-Benz US International (MBUSI) has said that it will upgrade its logistics and IT systems “to create a seamless integration of the supply base into the Mercedes-Benz plant operations”.

MercSUVlores-300x225

“In the next years we [will] invest $1.3 billion into the expansion of our SUV production and turn the Mercedes-Benz plant Tuscaloosa into a high-tech location,” said Markus Schäfer, member of the Divisional Board Mercedes-Benz Cars, Manufacturing and Supply Chain Management. “In this way we can produce the next SUV generations even more flexibly, efficiently and in proven top quality.”

The company said it would not provide any more details about the logistics upgrade but the wider plans include the addition of a 125,000 sq.m body shop that will use the latest lightweight technologies and employ a modular approach to manufacturing. MBUSI’s current SUV assembly shop will be expanded by 13,000 sq.m and receive a larger, more flexible marriage station, where the body is merged with the powertrain, allowing for production of a wider range of vehicles.

The latest expansion is part of MBUSI’s plan to make next SUV generations including the hybrid versions. It already produces the GLE (formerly M-Class), GL and C-Class sedan for the North American. Last month it moved production of the R-Class contract manufacturer AM-General in Mishawaka, Indiana to free production capacities to be used for the SUV series.

MBUSI produced more than 232,000 vehicles in 2014 and is on track to exceed 300,000 vehicles in 2015.

In a statement the company said that as part of its global production network, Tuscaloosa was connected to all Mercedes-Benz Cars locations around the world, allowing a location-independent access to data and process management.

“Every single installation and every robot, for example, can be controlled and updated to new software programmes,” said the company in a statement. “Big Data applications will be used for intelligent analyses and for an improvement of the production processes.”