ArticleMaterials (Basel, Switzerland)2023
Response Surface Methodology (RSM) Approach for Optimizing the Processing Parameters of 316L SS in Directed Energy Deposition.
Article in Materials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Machine Learning-Assisted Optimisation of the Laser Beam Powder Bed Fusion (PBF-LB) Process Parameters of H13 Tool Steel Fabricated on a Preheated to 350Materials (Basel, Switzerland) · 2026Article
- Tailoring Bayesian Additive Regression Trees (BART) for environmental mixture studies.PloS one · 2026Article
- Forming Process Prediction Model and Application of Laser Cladding for Remanufactured Screw Pump Rotors.Materials (Basel, Switzerland) · 2025Article
- Optimization Role of Potassium Carbonate in the Leaching of Guizhou's Carlin-Type Gold Ore System with Potassium Chlorate.ACS omega · 2024Article
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Authors and funding
6 authors.
Funding
Abstract
Directed energy deposition (DED) is a crucial branch of additive manufacturing (AM), performing repairs, cladding, and processing of multi-material components. 316L austenitic stainless steel is widely used in applications such as the food, aerospace, automotive, marine, energy, biomedical, and nuclear reactor industries. Nevertheless, there is need for process parameter optimization and a comprehensive understanding of the individual and complex synergistic effects of process parameters on the geometry, microstructure, and properties of the deposited material or component. This is essential for ensuring repeatable manufacturing of parts across a single or series of platforms over time, or for minimizing defects such as porosity. In this study, the response surface methodology (RSM) and central composite design (CCD) were employed to investigate the effects of laser power, laser scan speed, and powder mass flow rate on layer thickness, density, microstructure, and microhardness of 316L steel processed by Laser Engineered Net Shaping (LENS
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