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Heat treatment for metal additive manufacturing
journal contribution
posted on 2023-02-08, 23:33 authored by Majid LalehMajid Laleh, E Sadeghi, RI Revilla, Qi Chao, N Haghdadi, AE Hughes, Wei XuWei Xu, I De Graeve, M Qian, I Gibson, Mike Yongjun TanMike Yongjun TanMetal additive manufacturing (AM) refers to any process of making 3D metal parts layer-upon-layer via the interaction between a heating source and feeding material from a digital design model. The rapid heating and cooling attributes inherent to such an AM process result in heterogeneous microstructures and the accumulation of internal stresses. Post-processing heat treatment is often needed to modify the microstructure and/or alleviate residual stresses to achieve properties comparable or superior to those of the conventionally manufactured (CM) counterparts. However, the optimal heat treatment conditions remain to be defined for the majority of AM alloys and are becoming another topical issue of AM research due to its industrial importance. Existing heat treatment standards for CM metals and alloys are not specifically designed for AM parts and may differ in many cases depending on the initial microstructures and desired properties for specific applications. The purpose of this paper is to critically review current knowledge and discuss the influence of post-AM heat treatment on microstructure, mechanical properties, and corrosion behavior of the major categories of AM metals including steel, Ni-based superalloys, Al alloys, Ti alloys, and high entropy alloys. This review clarifies significant differences between heat treating AM metals and their CM counterparts. The major sources of differences include microstructural heterogeneity, internal defects, and residual stresses. Understanding the influence of such differences will benefit industry by achieving AM metals with consistent and superior balanced performance compared to as-built AM and CM metals.
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Journal
Progress in Materials ScienceVolume
133Article number
101051Pagination
101051-101051Publisher DOI
ISSN
0079-6425Language
enPublisher
Elsevier BVUsage metrics
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