Additive manufacturing has a great potential for the development of innovative industrial applications in different domains, as it enables the production of complex shapes, topologically optimized structures, and high‐value‐added components with novel embedded functionalities that are difficult or even impossible to produce with traditional technologies. However, stringent quality standards and qualification requirements impose defect‐free and first‐time‐right capabilities that are still challenging to achieve with state‐of‐the‐art AM systems. This article discusses existing solutions and open challenges for quality modeling, monitoring, and control in AM

Quality Monitoring and Control in Additive Manufacturing

Colosimo, Bianca M.
2020-01-01

Abstract

Additive manufacturing has a great potential for the development of innovative industrial applications in different domains, as it enables the production of complex shapes, topologically optimized structures, and high‐value‐added components with novel embedded functionalities that are difficult or even impossible to produce with traditional technologies. However, stringent quality standards and qualification requirements impose defect‐free and first‐time‐right capabilities that are still challenging to achieve with state‐of‐the‐art AM systems. This article discusses existing solutions and open challenges for quality modeling, monitoring, and control in AM
2020
Wiley StatsRef: Statistics Reference Online
9781118445112
quality, statistical process monitoring, statistical process control (SPC), additive manufacturing, 3D printing, in-situ monitoring, quality control, machine learning, profile, image, video
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1141276
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