Abstract
Additive Manufacturing (AM) is considered one of the key technologies for realizing Industry 4.0. There are numerous stages in the end-to-end AM process, including component design, material design, build, and so on. An enormous amount of data is generated along the end-to-end AM process that can be acquired from the 3D printer in real-time, micro-characterization studies, and process plan details, among others. For instance, these data can be employed to predict the printed components’ quality and, at the same time, proactively adapt the 3D printer parameters to achieve better quality. This end-to-end AM process can be mapped onto the digital thread. The current article elaborates on a conceptual framework to acquire the data from various sources associated with the end-to-end AM process and realize monitoring and control of the end-to-end AM process, leading to an intelligent AM process.
Graphical Abstract
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