AI for increased process efficiency

The project's goal is to demonstrate AI-based process control based on automatic quality analysis in Nilar's and Surahammars Bruks' production that share a similar need to automate the inspection routines, which today require a lot of manual work. The project approach is to use AI algorithms on existing process data in the form of image and measurement data in real time from production flows to detect quality deficiencies in both product and process.

Machine learning and image analysis enable errors to be identified more efficiently and earlier in the process, leading to environmental and economic improvements. Projects aims to reduce material waste by >30% and manual work by >50% in the process step, as well as increase the exploitation of available process information. In addition, production costs are expected to decrease through lower labor costs per unit produced and a higher production rate through automation.

The project aims to implement AI-based quality control in Nilar's and Surahammars Bruks' production showcasing the potential of this new technology in true industrial conditions. The project will work to spread this knowledge and create interest on AI among industry with great potential to lead to new services and business models.