Surface Roughness Optimization of Selective Laser Melting Printed 17-4 PH Stainless Steel Parts

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Authors

  • Lincoln University College, Selangor - 47301 ,MY
  • School of Science and Engineering, Curtin University, Dubai - 345031 ,AE
  • Lincoln University College, Selangor - 47301 ,MY
  • Department of Mechanical Engineering, Nitte Meenakshi Institute of Technology, Bengaluru - 560064, Karnataka ,IN

DOI:

https://doi.org/10.18311/jmmf/2023/35123

Keywords:

Pareto ANOVA, SLM Process, Surface Roughness, Taguchi Method, 17-4 PH Stainless Steel

Abstract

The 17-4 PH stainless steel possesses distinguished applications due to its inherent properties. Higher surface roughness in Selective Laser Melting (SLM) parts limits their use in a wide range of applications. Higher surface roughness deteriorates the important functional properties (strength, fatigue, corrosion resistance and so on). Therefore, an attempt is being made to reduce the surface roughness during the processing stage itself, rather than the dependency of costly secondary post-processing routes. Taguchi L9 experiments are conducted to analyze the laser power, scan speed and hatch distance influence on the surface roughness of SLM parts. Laser power showed the highest percentage contribution equal to 83.37%, followed by scan speed of 9.92% and hatch distance of 6.71%, respectively. Taguchi method determined optimal conditions (laser power: 270 W, scan speed: 1000 mm/s and hatch distance: 0.08 mm) through Pareto analysis of variance resulted in low values of surface roughness with a value equal to 4.11 µm. The results of the optimal condition can be used by any novice user to obtain better surface quality in SLM parts. Further, the Taguchi method can be applied to optimize any process with limited experimental trials and resources.

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Published

2023-12-01

How to Cite

Sahadevan , P., Selvan, C. P., Bhaumik, A., & Lakshmikanthan, A. (2023). Surface Roughness Optimization of Selective Laser Melting Printed 17-4 PH Stainless Steel Parts. Journal of Mines, Metals and Fuels, 71(12), 2405–2413. https://doi.org/10.18311/jmmf/2023/35123
Received 2023-09-17
Accepted 2023-12-18
Published 2023-12-01

 

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