German automotive supplier ZF is looking to withdraw from a joint $3bn (€2.78bn) microchip manufacturing project with US chipmaker Wolfspeed in western Germany, reported Reuters.
This decision comes as Wolfspeed paused the project due to weaker than anticipated demand for semiconductors and uncertainties about the viability of entering the European market, sources familiar with the development told the publication.
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ZF was poised to invest $185m for a share in the Saarland facility, aimed at producing chips for electric vehicles.
Wolfspeed had announced the plant and a research and development centre in Germany in February 2023.
The potential shelving of the project could be another blow to German initiatives to promote the country as a prime business location.
ZF has refuted claims that it caused delays in the project and has withheld comments on its alleged withdrawal.
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By GlobalData“Wolfspeed is responsible for the project. ZF has always provided intensive and active support,” stated a ZF spokesperson via email.
Representatives from Wolfspeed and the German economy ministry were unavailable to comment on the matter.
The sluggish pace of electric car demand is exerting pressure on ZF, which has revealed plans to cut a quarter of its 54,000 jobs in Germany by 2028 and recently revised its profit forecast downwards.
In a statement, ZF said: “The accelerated, significant market decline and the associated sharp drop in customer call-offs lead to an adjustment of ZF’s annual forecast.”
ZF also citing a reassessment of risks in the powertrain technologies business as a factor for reduced earnings expectations.
For the financial year 2024, ZF now anticipates group sales to range between €40bn and €42bn, down from the previously projected €42.5bn to €43.5bn.
The adjusted EBIT margin is forecasted to be between 3% and 4%, a decrease from the earlier estimate of 4.9% to 5.4%.
In September, ZF, in collaboration with Infineon Technologies, integrated artificial intelligence (AI) algorithms for vehicle software development and control within the EEmotion project.
These AI algorithms, tested in a vehicle, are designed to manage and optimise all actuators for automated driving according to the set driving trajectory.
