Panasonic, CATL, and GM/LG Energy Invest US$13 Billion in New Battery Factories and Machine Tool Builders like TRUMPF Will Help Fill Them

The global share of Electric Vehicles (EVs) nearly doubled in 2021, and continued growth is driving investment into new battery manufacturing sites. Prominent examples include Panasonic Energy’s US$4 billion factory in Kansas, CATL’s 7-billion-euro factory in Hungary, and GM/LG Energy’s US$2.3 billion Ohio plant. Furthermore, as of 2022, 111 industrial battery projects were being developed across EU member states. Many of the increasing number of new battery manufacturing plants are greenfield sites, such as Panasonic’s Kansas plant, meaning they are unburdened by legacy equipment investment and require significant investment in new tools for new tasks. Increasingly, these machine tools will be smart and connected, compelling a long tail of machine tool vendors to rethink their software and technology posture.

Laser machines are critical for battery manufacturing, utilized for cutting, welding, and micro-structuring. Stringent safety requirements for batteries in vehicles mean that battery packs must be made from very strong aluminum, a material that is difficult to manufacture with. As these batteries cannot be replaced, any work done on them needs to extend the full life of the vehicle, or risk high costs for manufacturers in recalls. Therefore, the use of high-powered laser welders is almost mandatory to ensure the correct product quality with reasonable feed speeds.

TRUMPF’s new laser machine tools are an excellent example of how new technologies are leveraged to ensure quality. Their lasers have smart sensors which can automatically check the seam quality during the welding process, both reducing scrap material and time spent on quality inspection. The company states that with their lasers they are able to make battery packs 100% airtight, extending life and increasing safety. While the lasers are required simply to work with the aluminum, a key underlying change is the software and sensors that underpin the machine. Quality assessment using machine vision and sensors, supported by data analytics is what enables these machines to meet the stringent requirements of the EV sector and differentiates them from legacy automated lasers. Furthermore, manufacturers who construct new plants will be looking to build smart factories and will require their machines to connect and share data with a networked digital thread to maximize Overall Equipment Effectiveness (OEE). With the high production requirements, alongside the OEE improvements provided by these new machine tools, this has led to a sharp increase in demand, and in 2021, TRUMPF sold more than 1000 lasers for battery production.

To see success in the coming years, machine tool builders need to invest in being able to supply customers with comprehensive supporting software as well as provide manufacturers with truly turn-key solutions that can easily integrate into the digital threads that are being built. They can either design this software themselves or choose to strategically partner with technology vendors who already produce the software. However achieved, the end goal is for machine tool builders to provide manufactures with an ecosystem solution rather than a discrete asset. TRUMPF have shown that the combination of new sensors and software in their lasers has resulted in strong investment from battery manufacturers, and as the market grows, other machine tool builders must adopt and extend this new machine tool model, viewing their offering as a solution rather than a discrete product. 

As machine builders improve their software posture, they will continue to rely more heavily on technology vendors such as Siemens, Rockwell Automation, and Dassault Systemes to construct data management, cloud, and industrial network solutions. It is in the interest of these technology vendors to provide the widest range of end-to-end solutions, rather than highly specialized offerings. In this case, the best solution is having broadest solution set with the least gaps. The offerings need to be able to scale up and down with demand, alongside not majorly impacting the total cost of the machine tool offering.