Chipmetrics set up Dresden-based subsidiary
Chipmetrics has officially launched its new Dresden-based German subsidiary, Chipmetrics GmbH. Originally hailing from Joensuu in Finland, 2025 is set to be an important year for the company as it aims to aggressively scale both sales and marketing of its 3D semiconductor metrology products.
Chipmetrics’ tool qualification efforts will get a boost from the added presence in Silicon Saxony.
“Dresden is Europe’s most important semiconductor location, and formally being here with Chipmetrics is going to open up doors for us,” says Thomas Werner, Head of metrology wafer business, in a press release. “The German entity allows us to not only better serve our European clients and develop business here, but as we’re expanding it also allows us to hire people who are perhaps better integrated into the 300-millimeter semiconductor ecosystem than we could in Finland.”
With the expansion plans for 2025, Chipmetrics' is looking to grow its numbers and is actively seeking to fill positions such as COO (Chief Operating Officer), Sales Manager and ALD Scientist – all positions available in either Dresden or Finland.
Chipmetrics’ main products aim to address some of the most pressing challenges in modern semiconductor manufacturing. As component structures shrink to near-atomic scales, the industry increasingly embraces three-dimensional chip architectures. Thin layers are deposited using Atomic Layer Deposition (ALD) – a technology originally pioneered in Finland in 1974 – to reliably coat deep chip structures with extraordinary precision.
The ability to accurately measure ALD data in 3D structures with high aspect ratios aids both R&D efforts for future chips such as 3D DRAM as well as tool qualification and process control.
“AI and Machine Learning are here to stay, especially in automated production processes as the ones we see in semiconductors. With our metrology chips and wafers, we can speed up the tool qualification process, minimizing downtime as well as providing the best possible data to train AI/ML models on.” continues Werner.
