Currently, we are using multiple AI systems in our production process. The AI systems have been developed in-house and through collaborations, such as with RISE. As a result of implementing AI, we have experienced a significant increase in efficiency and the ability to identify potential defects. This allows us to maintain a high quality in the battery module production, and we continue to explore new ways to integrate AI into our production process.
In the video, you can see when we presented our technology to Mats Persson, Swedish Minister for Education. The AI system shown has been developed in partnership with RISE and is used as part of battery module production. The AI system captures thousands of images per day. This technology enables traceability to earlier module configurations with its advanced image analysis, which would be impossible to achieve manually. This provides us with high quality control that could not be done before as the AI checks images of each layer in the module to detect potential defects.
– In production we see significant benefits with AI driven built-in technology. It helps us to make faster and more repetitive decisions in the facility while also allowing for better rotation of work positions, says Jim Wennmark, Production Manager at Nilar International AB.
Furthermore, we also developed our own AI model with the help of a statistician who was curious about this area, Gustav Thunström, Data Analyst at Nilar. This AI model was inspired by the previous project with RISE and uses data from the curves in the formation process to detect defects. By identifying errors more efficiently and earlier in the process, we can enhance our environmental and economic sustainability.