Automation in a large scale in the glass tempering is still in its infancy, as the industry has long relied on a skilled manually operating workforce to ensure the highest quality products. However, with intensifying labour shortages and growing industry challenges, there is a great need for automation in this sector.
Automation has the potential to handle up to 90% of the tasks on a mixed production tempering. The remaining special glasses can then be managed manually. By combining the strengths of both automated and manual approaches, optimal efficiency and versatility can be achieved. This allows the flexibility to switch from automation to manual operation that is essential to address unique or complex tasks.
The benefits of automation are particularly pronounced with technologies like state-of-the-art robotized loading systems. These systems optimize batch loads and demonstrate remarkable efficiency in handling diverse glass thicknesses and sizes.
First 6-axis robot, Stanford Arm, was invented 1969. Ever since robotics has been utilised widely and successfully, also with glass processing nothing really new. Why not with mixed production of glass tempering? In my paper I shall expose the case further by emphasizing the possibilities with an algorithm for efficient AI-assisted batch building, i.e. analysis of the properties of the glass flow from preprocessing and tuning process parameters based on furnace properties and learnings of the process parameters used earlier.
