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This is the fifth and last part of a series by Ashley Stone and Edo Meyer that will take you through the development of the digital foundry and give you an overview of the state of the magnesium die casting industry.
Did you miss the part before?
Find the article about the four semisolid metal casting processes here.
The novelty of this invention is in the way of generating and using additional set of variables of the inspected actual parts with the intention of iteratively starting the process automatically and speeding up the process to obtain good production parts with minimum losses of energy and materials.
The concept of a fully automated die casting process means that a casting machine and an X-ray machine work in tandem. The operator only needs to turn on the machine, select the 3D part to be cast, make sure the material is available and remove the cast parts. For example, the die cast wheel for a car would follow a basic sequence like this:
1. The operator would power up the semisolid casting machine, follow an initial checklist related to material supply and safety verification, choose the part to be produced, and then press the start button.
2. The new semisolid casting machine would begin casting the first wheel based on the proposed initial process parameter data set coming from casting simulation database, and upon completion, the wheel would be immediately inspected at the X-ray inspection system.
3. The fully automated X-ray inspection system would determine the quality of the wheel and generate the digital model of the now uniquely identified part for the life of the part.
4. If the part is good, all the information about this good wheel will be stored in a good wheel record database. The same process would be followed for the original production (process) data set as well as the design 3D model data set.
5. If the wheel is bad, the information is stored in a bad wheel record database. Assuming that the wheel is bad, the knowledge system will determine which set of parameters must be iteratively adjusted to improve the wheel's poor characteristics, and a new set of inputs will be generated in the parameter generator.
By way of a hypothetical example, the inspection may indicate that the wheel is not completely formed; indicating insufficient feedstock has been injected into the mold, commonly referred to as a short shot. The knowledge system determines a longer injection period is appropriate, and iteratively instructs the parameter generator to delay the closing of the nozzle.
6. The next machine cycle is executed, serialized, and passed on to the inspection system.
More data from the inspection system generates more information and allows faster convergence to a set of parameters that produce good quality wheels. This process for manufacturing magnesium wheels by closing the loop with data from an inspection system and accelerating convergence with data sets of good and bad wheels as well as a 3D digital model of the original design will enable the production of high integrity wheels with minimal scrap. The fully automated process will generate the intelligence necessary to run the process and maintain high quality production at all times.
This is an intrinsically safe, energy efficient, environmentally friendly magnesium casting plant with no gas emissions outside plant parameters. All of the casting machines and X-ray inspection equipment, as well as the proprietary linear robotics and vision systems integrated into this semisolid state die casting process, ensure rapid production of good parts and maintain stable, automatic, closed-loop process control. The collection of process data for the same or similar parts worldwide will be via the cloud, and anyone can use it.
