Paper Contents
Abstract
Additive manufacturing (AM) has revolutionized the production of complex geometries and high-performance components, particularly in the realm of metal alloys. However, achieving optimal mechanical properties while ensuring cost-effective production remains a challenge. This study focuses on the optimization of additive manufacturing processes for high-performance metal alloys, with an emphasis on process parameters such as laser power, scanning speed, and layer thickness. By using a combination of experimental analysis and computational modeling, the study evaluates the effects of these parameters on the microstructure, density, and mechanical performance of metal alloy parts. Special attention is given to the trade-offs between strength, ductility, and surface finish. Through the development of predictive models, we aim to identify optimal process conditions that enhance material performance while reducing manufacturing defects such as porosity and residual stresses. The findings of this study provide valuable insights for improving the quality and efficiency of metal additive manufacturing, enabling its broader application in industries like aerospace, automotive, and biomedical engineering
Copyright
Copyright © 2024 Md. Saifur Rahman. This is an open access article distributed under the Creative Commons Attribution License.
