Siemens announced an investment of $150 million in a new high-tech manufacturing plant in Dallas-Fort Worth to help power American data centers and critical infrastructure. This plant will produce electrical equipment.
The facility will enable accelerated growth of U.S. data centers, which is being driven by the exponential adoption of generative AI. It will also ensure secure operation of critical infrastructure.
This investment specifically supports long-term customers in the data center space, where demand is expected to grow by around 10% annually through 2030.
“The hardware and software we offer will ensure that growing industries can meet demand while continuing to make progress in decarbonizing operations,” said Roland Busch, President and CEO of Siemens AG. “With this latest step, Siemens is delivering on its €2 billion global investment strategy for 2023 to boost growth, innovation and resilience.”
New projects create a total of around 1,700 jobs in the U.S.
As part of these investments, Siemens announced a $220 million investment in a new rail manufacturing facility in Lexington, North Carolina, earlier this year. Construction of this facility is now underway.
In addition, the company is investing in two electrical-products manufacturing plants in Grand Prairie, Texas, and Pomona, California. These projects bring the overall investment in the U.S. this year to $510 million, which will create 1,700 jobs.
The new Fort Worth facility and the Grand Prairie and Pomona extensions will meet demand for the electrification of critical infrastructure.
Production at the new facility in Fort Worth is expected to start in calendar year 2024, gearing up for full operations in 2025. This factory will be built and operated using Siemens advanced manufacturing tools, including digital twin technology and high-tech automation to ensure the highest quality, efficiency and sustainability levels.
The Siemens Xcelerator portfolio will be used to capture and analyze data from the shopfloor on production and product performance in real time.