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As a supplier of mechatronic solutions for the processing of steel sheets, Clecim has recently extended its range of laser welders by offering a new generation machine capable of cutting and welding heavy sheets by means of a 12kW laser source. . In 2019, the laser cutting process was widely studied and the use of Machine Learning techniques made it possible to create a model capable of delivering robust cutting instructions for the entire thickness range. Today, attention is focused on the autogenous laser welding process (without filler wire). Obtaining a good weld requires fulfilling two criteria: having a weld bead free of defects (types of spatter, drips, underfilling, holes, etc.), and having good resistance (this is evaluated via a stamping test of the Erichsen type, the objective being to be as close as possible to the basic resistance of the material). To achieve this result, many steps have been implemented, each requiring the use of a JMP platform:
"Fit X by Y" and "Distribution" to not only statistically determine the value of the base strength of the material, but also to ensure that the sheets studied can be considered identical and homogeneous
"Graph Builder" to synthesize the visual observations and obtain a map of the welding defects according to the parameters studied, the result making it possible to determine an area where the weld bead is free of defects
And finally, "DoE/Custom Design" and 2 Fit Model" which allow you to study and model the resistance of the weld bead on the previous zone in order to determine the optimal parameters. Since the study area is irregular in shape, it is filled in as a set of candidate points (Covariates)
This post originally written in French and has been translated for your convenience. When you reply, it will also be translated back to French .
This post originally written in French and has been translated for your convenience. When you reply, it will also be translated back to French .