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'''The Vision''' of the aiCAMstir project came-up during a friction stir welding training course in Munich.
'''The Vision''' of the aiCAMstir project came-up during a friction stir welding training course in Munich.
Some years ago, [[USer:STephan Kallee at AlusStir|Stephan Kallee]] had worked on a project on making tailor welded blanks by friction stir welding. A new spindle, a new jig, two FSW experts and a new technician were available, who was experienced in operating milling machines but had not received in-depth training on parameter optimisation. Due to a business trip, they worked on three different sites: in the lab, in the office and in a hotel. They could only communicate by mobile phone, sharing photos and information on the parameter settings. After a few iterations, optimised parameters could be found.
Some years later, he came-up with the idea on using neuro-networks for optimising FSW parameters. During a training course in Munich, the concept of using artificial intelligence in computer aided manufacturing was discussed in more detail and a project with very promising results was conducted.
In the aiCAM<sup>''stir''</sup> project we want to go one step further. We want to create a cloud, into which FSW operators can upload images and information on parameter settings during feasibility studies, prototyping, production ramp-up and series production, and get feedback about the weld quality and recommendations on optimising the parameters. In the final stage, such a system would be integrated into the FSW machine , and the machine would optimise the parameters itself within boundries set by the operator.

Revision as of 10:57, 16 April 2021

Three friction stir welds made during a training course in Munich

The Vision of the aiCAMstir project came-up during a friction stir welding training course in Munich.

Some years ago, Stephan Kallee had worked on a project on making tailor welded blanks by friction stir welding. A new spindle, a new jig, two FSW experts and a new technician were available, who was experienced in operating milling machines but had not received in-depth training on parameter optimisation. Due to a business trip, they worked on three different sites: in the lab, in the office and in a hotel. They could only communicate by mobile phone, sharing photos and information on the parameter settings. After a few iterations, optimised parameters could be found.

Some years later, he came-up with the idea on using neuro-networks for optimising FSW parameters. During a training course in Munich, the concept of using artificial intelligence in computer aided manufacturing was discussed in more detail and a project with very promising results was conducted.

In the aiCAMstir project we want to go one step further. We want to create a cloud, into which FSW operators can upload images and information on parameter settings during feasibility studies, prototyping, production ramp-up and series production, and get feedback about the weld quality and recommendations on optimising the parameters. In the final stage, such a system would be integrated into the FSW machine , and the machine would optimise the parameters itself within boundries set by the operator.