Investigation About the Warm Deep Drawing of Mg Alloys Using Metamodels
CHALLENGE - Lower fuel consumption and limited emissions are one of the main concerns of the automotive sector and can be achieved by vehicle lightweighting, i.e. adopting alloys with lower density and higher strength. Magnesium alloy is among the lightest materials, but has limited formability at room temperature.
SOLUTION - Experimental tests were carried out to investigate which parameters affect magnesium alloy formability the most: temperature was revealed as one of the most influencing parameters in terms of alloy drawability. The first experimental data were imported in modeFRONTIER to train reliable response surfaces and perform a virtual optimization, whereas the second experimental campaign was aimed at understanding the influence of the most important parameters on the alloy drawability and validating the first results.
BENEFITS - Engineers were able to try out different response surface strategies available in modeFRONTIER to increase their knowledge of the problem. The chosen algorithm was sufficiently reliable to produce robust results and maximize the process performance.