Process optimization and mechanical properties analysis of Inconel 718/stainless steel 316 L multi-material via direct energy deposition

Yu Xiang Chen, Jun Ru Qiu, Wei Ling Chang, Yi Kai Hwang, Sheng Jye Hwang

Research output: Contribution to journalArticlepeer-review

Abstract

Additive manufacturing (AM), also known as 3D printing, is a recent innovation in manufacturing, employing additive techniques rather than traditional subtractive methods. This study focuses on Directed Energy Deposition (DED), utilizing a blend of nickel-based superalloy IN 718 and stainless steel SS316 powders in varying ratios (25%+75%, 50%, and 75%+25%). The objective is to assess the impact of process parameters on quality and optimize them. Mechanical properties of the different powder mixtures are compared. In the study, Taguchi-grey relational analysis is employed for parameter optimization, with four key factors identified: laser power, overlap ratio, powder feed rate, and scanning speed, affecting cladding efficiency, deposition rate, and porosity. Verification experiments confirm optimization repeatability, and further fine-tuning is achieved through one-factor-at-a-time experiments. Optimized parameters yield varied tensile properties among different powder mixtures; for example, a 25% SS316L and 75% IN718 blend demonstrates the highest ultimate tensile strength (499.37 MPa), while a 50% SS316L and 50% IN718 blend exhibits the best elongation (13.53%). This study offers an effective approach for using DED technology to create mixed SS316 and IN718 powders, enabling tailored mechanical performance based on mixing ratios.

Original languageEnglish
Article number28927
JournalScientific reports
Volume14
Issue number1
DOIs
Publication statusPublished - 2024 Dec

All Science Journal Classification (ASJC) codes

  • General

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