Optimising surface roughness and density in titanium fabrication via laser powder bed fusion

Journal article

Hassanin, H., El-Sayed, M., Ahmadein, M., A. Alsaleh, N., Ataya, S., Ahmed, M. and Essa, K. 2023. Optimising surface roughness and density in titanium fabrication via laser powder bed fusion. Micromachines. 14 (8), p. 1642. https://doi.org/10.3390/mi14081642
AuthorsHassanin, H., El-Sayed, M., Ahmadein, M., A. Alsaleh, N., Ataya, S., Ahmed, M. and Essa, K.
Abstract

The Ti6Al4V alloy has many advantages, such as being lightweight, formal, and resistant to corrosion. This makes it highly desirable for various applications, especially in the aerospace industry. Laser Powder Bed Fusion (LPBF) is a technique that allows for the production of detailed and unique parts with great flexibility in design. However, there are challenges when it comes to achieving high-quality surfaces and porosity formation in the material, which limits the wider use of LPBF. To tackle these challenges, this study uses statistical techniques called Design of Experiments (DoE) and Analysis of Variance (ANOVA) to investigate and optimise the process parameters of LPBF for making Ti6Al4V components with improved density and surface finish. The parameters examined in this study are laser power, laser scan speed, and hatch space. The optimisation study results show that using specific laser settings, like a laser power of 175 W, a laser scan speed of 1914 mm/s, and a hatch space of 53 µm, produces Ti6Al4V parts with a high relative density of 99.54% and low top and side surface roughness of 2.6 µm and 4.3 µm, respectively. This promising outcome demonstrates the practicality of optimising Ti6Al4V and other metal materials for a wide range of applications, thereby overcoming existing limitations and further expanding the potential of LPBF while minimising inherent process issues.

KeywordsLaser powder bed fusion; Design of experiments; Ti6Al4V; ANOVA; Process parameters
Year2023
JournalMicromachines
Journal citation14 (8), p. 1642
PublisherMDPI
ISSN2072-666X
Digital Object Identifier (DOI)https://doi.org/10.3390/mi14081642
Official URLhttps://www.mdpi.com/2072-666X/14/8/1642
Publication dates
Online20 Aug 2023
Publication process dates
Accepted15 Aug 2023
Deposited05 Oct 2023
Publisher's version
License
File Access Level
Open
Output statusPublished
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