MetaPrinter: A Digital Twin-Enabled Platform for 3D Printer Diagnostics

In the age of digitalization, virtually everything around us is on the cloud. The metaverse allows people to perform the things they do in the real and virtual worlds. In the virtual world of the metaverse, everything from work to communication is on demand and connected. One of the advantages of the metaverse is the lack of physical barriers in development. Performing tests on expensive equipment are no longer expensive because companies do not have to purchase physical hardware. In addition, the risks in performing tests are virtually eliminated. Hardware errors may cause damage to a physical system, but in a metaverse, all one needs to do is reboot the virtual machine and have it reloaded with an operating system. In additive manufacturing, testing a 3D printer may take time and resources. Furthermore, miscalculations and unfavorable environmental conditions may lead to printing issues. Developing a simulation tool to test a 3D printer in variable environments is explored to address possible problems with additive manufacturing. The behavior of the digital twin will be diagnosed using various deep learning algorithms implemented in various studies. CNN-BiLSTM has proven to be the most accurate of the deep learning algorithms explored.