ARTIFICIAL INTELLIGENCE FOR QUALITY CONTROL IN ADDITIVE MANUFACTURING: METHODS, METRICS AND INDUSTRIAL READINESS

Sven MARICIC, Mihael HOLI

Abstract


Artificial intelligence (AI) is transforming quality control in additive manufacturing (AM) by introducing automation, predictive analysis, and higher accuracy throughout the production process. AI-powered methods address common 3D printing challenges such as defect detection, process variability, and equipment failures, enabling more reliable and efficient manufacturing. This paper reviews key applications of AI in AM quality control from 2018–2025, focusing on defect detection, predictive maintenance, and process optimization. The contribution of this study lies in mapping methods to AM processes, reporting performance outcomes, and identifying current limitations for industrial adoption.

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References


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