Optimizing Selective Laser Melting of Inconel 625 Superalloy through Statistical Analysis of Surface and Volumetric Defects

Author:

Shahrjerdi Ali1,Karamimoghadam Mojtaba2ORCID,Shahrjerdi Reza3,Casalino Giuseppe2ORCID,Bodaghi Mahdi4ORCID

Affiliation:

1. Mechanical Engineering Department, Malayer University, Malayer 7R7X+8M5, Iran

2. Department of Mechanics, Mathematics and Management, Polytechnic University of Bari, Via Orabona 4, 70125 Bari, Italy

3. Department of Industrial, Mechanical and Aerospace Engineering, Buin Zahra Technical and Engineering University, Buin Zahra Q346+GVC, Iran

4. Department of Engineering, School of Science and Technology, Nottingham Trent University, Nottingham NG11 8NS, UK

Abstract

This article delves into optimizing and modeling the input parameters for the selective laser melting (SLM) process on Inconel 625. The primary aim is to investigate the microstructure within the interlayer regions post-process optimization. For this study, 100 layers with a thickness of 40 µm each were produced. Utilizing the design of experiments (DOE) methodology and employing the Response Surface Method (RSM), the SLM process was optimized. Input parameters such as laser power (LP) and hatch distance (HD) were considered, while changes in microhardness and roughness, Ra, were taken as the responses. Sample microstructure and surface alterations were assessed via scanning electron microscopy (SEM) analysis to ascertain how many defects and properties of Inconel 625 can be controlled using DOE. Porosity and lack of fusion, which were due to rapid post-powder melting solidification, prompted detailed analysis of the flaws both on the surfaces of and in terms of the internal aspects of the samples. An understanding of the formation of these imperfections can help refine the process for enhanced integrity and performance of Inconel 625 printed material. Even slight directional changes in the columnar dendrite structures are discernible within the layers. The microstructural characteristics observed in these samples are directly related to the parameters of the SLM process. In this study, the bulk samples achieved a microhardness of 452 HV, with the minimum surface roughness recorded at 9.9 µm. The objective of this research was to use the Response Surface Method (RSM) to optimize the parameters to result in the minimum surface roughness and maximum microhardness of the samples.

Publisher

MDPI AG

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