Vision systems for quality inspections in production processes have existed for a long time, but are currently used only to a limited extent and then primarily within manual assembly lines. Within the VISION project, we aim to develop a low-cost, high-performing vision system for automated quality inspections in assembly lines based on cheap hardware and state-of-the-art machine learning algorithms for real-time image processing.
The motivation behind the project is to enable the use of automated quality inspections within the Swedish production industry on a massive scale in order to reduce, or even eliminate, quality defects in manual assembly processes. Besides increased quality, a driver behind the project is to lower production costs through avoiding the need to manage rejects and being able to replace today’s manned quality inspection stations with automated inspections along the production line, which will also enable shorter lead times.
Delivering off-the-self cameras
The project will develop a fully functional solution that will be evaluated in a number of industrial test cases. It will also be implemented in a publicly available demonstrator at ASSAR. To ensure that any company, regardless of size, can easily install and afford the solution, the vision system will be designed for cheap off-the-shelf cameras costing less than SEK 300. The system will be published as open source software available for anyone to download and use without cost.
Having a real impact
It can be noted that for any solution to have a real impact, the solution must be technologically feasible, beneficial for the user and contribute to production system competitiveness. These three dimensions of the solution developed in the project will therefore be explored and evaluated as part of the project.
When we succeed in developing this solution, we will have contributed to increasing
- The competitiveness of Swedish industry
- The use of automation in Swedish manufacturing industries
- The cost-effectiveness of Swedish manufacturing industries
- The use of digital technologies
- Economic and social sustainability.