Work

Data-driven modeling of process-structure-property relationships in metal additive manufacturing

Year: 2024

Type: article

Abstract: Metal additive manufacturing (AM) faces challenges in rapid selection and optimization of manufacturing parameters for desired part quality. As a more efficient alternative to experiments and high-fidelity physics-based models, data-driven modeling is effective in understanding process–structure–property relationships. This brief review explores data-driven modeling in metal AM, focusing on “process”, “structure”, and “property”, further identifying limitations in current applications and accordingly presenting future outlook on the possible advancements in this domain.

Source: npj Advanced Manufacturing

DOI: 10.1038/s44334-024-00003-y

Authors: Zhaoyang Hu, Wentao Yan

Institution: National University of Singapore

Language: English

Topic: Additive Manufacturing Materials and Processes

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $2,490