CPT International 02/2021
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CASTING TECHNOLOGY<br />
Figure 7: Schematic of light<br />
alloy wheels self-learning<br />
smart factory incorporating<br />
MAXImolding machine with<br />
feed back x-ray control loop<br />
incl. ADR software and<br />
knowledge system for data<br />
analyzing and prediction of<br />
process parameters<br />
tors to ensure the exchange of information<br />
between the participating devices.<br />
Any user can operate aMAXImolding<br />
process anywhere in the world and realize<br />
best parts possible. The objective is<br />
to apply these aspects to the casting cell<br />
and thus create safe and autonomous<br />
production. Figure 7shows the approach<br />
ofanintelligent production chain<br />
for discrete production. Foundries are<br />
being transformed into part production<br />
cells with unique supply chain and process<br />
optimization network.<br />
The entire production process for a<br />
light alloy wheel could look something<br />
like this: the operator selects the part to<br />
be molded from a3-D database and<br />
supplies power to the MAXImolding<br />
injection molding machine. Achecklist<br />
is followed with regard to material supply<br />
and safety checks, and then the<br />
machine isstarted. The MAXImolding<br />
machine suggests the startup process<br />
parameters and sets them. The machine<br />
operator confirms proposed parameters<br />
or set owns. Casting of the first wheel<br />
begins. After completion, the wheel is<br />
immediately inspected on the X-ray<br />
inspection system with Automatic<br />
Defect Recognition (ADR). This determines<br />
the quality of the wheel and generates<br />
adigital identifier that can be<br />
used to identify the part. If the part<br />
produced is found to be good, the associated<br />
process parameters are stored in<br />
adatabase and marked as „good.“<br />
Parameters of the defective products<br />
are also stored so that faster iterative<br />
adjustments to process parameters can<br />
be made from them. For example,<br />
inspection might show that the wheel<br />
was not fully formed, indicating insufficient<br />
starting material and commonly<br />
referred to as ashort shot. The system<br />
recognizes that alonger injection time<br />
is needed and iteratively instructs the<br />
parameter generator to delay closing<br />
the nozzle. The next machine cycle is<br />
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