Additive Manufacturing (AM), commonly known as 3D printing, is changing the way products are being designed, manufactured and maintained. Almost everything around us has been created in a factory and was partly made possible innovations in manufacturing processes. AM refers to a process in which digital 3D design data is used to build up a component in layers by depositing material. Even though most of the cornerstone AM processes were invented and first commercialized more than 25 years ago, Additive Manufacturing has only recently been widely considered for the manufacturing of end products. The following figure shows the process of AM.
The creation of 3D models is a highly complex task, which requires a lot of information and knowledge to create a 3D model out of the given framework conditions. To simplify the process, it is possible to use a 3D scanner if there is already an existing part. Then the user must only perform optimizations on the 3D model. Currently AI takes a supporting role in creating 3D models. One tool, which is driven by AI in many CAD programs, is a topology optimization tool. This tool can be used to optimize scanned 3D models or to verify surface models for gaps. Therefor the tool not just analyzes the geometry it also makes suggestions how to optimize it. Another way AI is implemented in a CAD environment is by using a DL algorithm which takes track on the steps which are done to create certain 3D models. With time the DL algorithm learns which steps are commonly followed by others, so that it can make suggestions on how to complete the 3D model (digitalengineering247, 2020).
Preprocessing which includes slicing is a very time and labor consuming part of AM processes. Especially in cases where printed parts have high requirements in shape or properties, only experienced engineers are suitable for this task, which increases the costs even more. Therefor preprinting evaluation tools based on AI are developed. The goals of these tools are to improve part consistency and reliability while also reducing labor, as well as production time and costs. In addition to this the tool can replace the otherwise required engineer, who – because of his human nature – is more susceptible to errors (Boissonneault, 2020).
Depending on the AM process, 3D printing can consist of several steps. In some cases, AM processes use sinter-based technologies which require sintering to give the printed part its final shape and material properties. The problem that arises through sintering is the deformation of the part in the process. This results into a trial-and-error phase during the production of every new designed part. To counteract this effect ML is used to precalculate the deformation and adjust the model accordingly. Thereby the production process can getshortened, and the costs can be lowered (Additive Intelligence, 2021).
Prepared by Institute for Product Development and Innovation, University of Applied Sciences Düsseldorf, Germany
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