Sinéad M. Uí Mhurchadha

Bio: Sinéad M. Uí Mhurchadha is an academic researcher from Waterford Institute of Technology. The author has contributed to research in topics: Materials science & Metal powder. The author has an hindex of 1, co-authored 2 publications receiving 2 citations.

Comparison of the porosity and mechanical performance of 316L stainless steel manufactured on different laser powder bed fusion metal additive manufacturing machines

Abstract: Despite the recent progress in additive manufacturing (AM) process and technology, challenges in the repeatability and reproducibility of AM parts still hinders the adoption of this technique in many industries. This is particularly difficult when a part is qualified on a particular part on a certain machine using optimised parameters. If a manufacturer wishes to expand production to multiple machines, the ability to translate these optimised parameters to different machines much be understood. In this study, four different metal L-PBF printers were used to produce 316L tensile testing samples using the same processing parameters and metal powder supplied from a single batch from the same supplier. In addition to the analysis of the correlation between the input parameters and the output measures, this study reports that despite the same set process parameters, there is significant variations were found in the mechanical performance and properties of the AM samples produced on the different L-PBF metal additive manufacturing machines. For the range of the input processing parameters and the resulting input volumetric energy density applied of 21–37 J/mm3, values of (4–42)%, (200–716) MPa, and (52–214) GPa were obtained for the elongation, ultimate tensile strength and elastic modulus on additively manufactured 316L samples respectively.

Development and Validation of Empirical Models to Predict Metal Additively Manufactured Part Density and Surface Roughness from Powder Characteristics

Abstract: Metal additive manufacturing (AM) processes, viz laser powder bed fusion (L-PBF), are becoming an increasingly popular manufacturing tool for a range of industries. The powder material used in L-PBF is costly, and it is rare for a single batch of powder to be used in a single L-PBF build. The un-melted powder material can be sieved and recycled for further builds, significantly increasing its utilisation. Previous studies conducted by the authors have tracked the effect of both powder recycling and powder rejuvenation processes on the powder characteristics and L-PBF part properties. This paper investigates the use of multiple linear regression to build empirical models to predict the part density and surface roughness of 316L stainless steel parts manufactured using recycled and rejuvenated powder based on the powder characteristics. The developed models built on the understanding of the effect of powder characteristics on the part properties. The developed models were found to be capable of predicting the part density and surface roughness to within ±0.02% and ±0.5 Ra, respectively. The models developed enable L-PBF operators to input powder characteristics and predict the expected part density and surface roughness.

The development of a smart additively manufactured part with an embedded surface acoustic wave sensor

Abstract: This paper presents the embedding of a temperature Surface Acoustic Wave (SAW) sensor in an additively manufactured 316L stainless steel part during the Laser Powder Bed Fusion (L-PBF) process. The embedding of sensors and integrated circuits in additively manufactured (AM) parts is an important step towards the development of smart components; however, there are still some barriers to overcome for this to become an established technology. The L-PBF process is paused to embed a SAW sensor in an AM part to produce a wireless and passive smart component. The effect of the pausing of the L-PBF process to embed sensors on the microstructure and hardness of the manufactured parts is investigated and the embedded sensor is also tested to verify its functionality. These results act as a proof-of-concept for the embedding of SAW sensors during the L-PBF process and will lead to the development of passive wireless smart components manufactured by additive manufacturing.

Characterization and Analysis of the Thermal Conductivity of AlSi10Mg Fabricated by Laser Powder Bed Fusion

Abstract: Laser-based powder bed fusion (L-PBF) of AlSi10Mg is used to fabricate complex, light-weight structures with high thermal conductivity. Much effort has gone into investigating the mechanical behavior of L-PBF components; however few studies investigated their thermal properties. This investigation characterizes the effect of process parameters on the relative density of AlSi10Mg components fabricated by L-PBF to understand how these parameters contribute to thermal conductivity. Exposure time, laser power, pointwise distance, and build orientation were examined. Results show that these parameters affect the effective thermal conductivity of printed parts by up to 22%. Pointwise distance had the most impact on melt pool size and on effective thermal conductivity compared with other parameters. As the pointwise distance increased, both the conductivity and the melt pool width decreased, whereas the laser power had a negligible effect on both. The effect of exposure time was mainly dependent on the pointwise distance. We show that thermal conductivity is not only related to the relative density of the samples, but the number of the melt pool boundaries in the microstructure also plays a significant role in interrupting the heat flow. A new factor which accounts for the number of melt pool boundaries per unit length in the direction of heat flow is introduced to quantify the phonon scattering associated with the microstructure evolution induced by the process parameter changes. This helps explain the variation in thermal conductivity for samples manufactured with high energy densities which had negligible difference in relative density.

Laser beam powder bed fusion of nitinol shape memory alloy (SMA)

Abstract: This study is focused on the 3D printing of NiTi shape memory alloy (SMA) in cuboidal shaped samples via the Laser Powder Bed Fusion (L-PBF) process using a dissimilar material build plate of 316L stainless steel. Four processing parameters were investigated at three levels for the optimization of the process. Those parameters were the laser beam power, scanning speed, laser beam spot size and hatch spacing. The produced samples exhibited varying levels of bonding with the substrate. Compression testing, Archimedes density measurement and EDX chemical composition were carried out. A design of experiment model was developed relating the input process parameters to the output properties. The effect of the calculated volumetric energy density and the sample melt-pool temperatures on the output measures were also investigated for the strong bonding and weldability with the substrate metal.

Laser surface polishing of Ti-6Al-4V parts manufactured by laser powder bed fusion

Abstract: Poor surface quality of Additively Manufactured (AM) components, can greatly increase the overall cost and lead time of high-performance components. Examples are medical devices where surfaces may contact the patient's skin and hence need to be smooth and aerospace components with high fatigue strength requirements where surface roughness could reduce fatigue life. The average surface roughness (Ra) of AM parts can reach high levels greater than 50 μm and maximum distance between the high peaks and the low valleys of more than 300 μm. As such, there is a need for fast, cost effective and selective finishing methods of AM produced components targeted at high-performance industries. In this paper Ti-6Al-4V Grade 23 ELI, popular for medical devices and aerospace parts production, was L-PBF processed to manufacture parts which were subsequently treated via laser polishing. Here in this work, CO 2 laser polishing was used for the surface modification of the Ti-6Al-4V produced samples. The most significant processing parameters were optimised to achieve approximately an 80% reduction in the average surface roughness and a 90% reduction in the peak-to-valley distance with a processing time of 0.1 s/mm 2 and cost of 0.2 €/cm 2 . • CO 2 laser polishing of additively manufactured Ti-6Al-4V is presented. • Flat and cylindrical samples were successfully polished by using the methodology detailed in this article. • The percent overlap of the laser scanning track was an effective processing parameter to reduce surface roughness. • Double-pass lasing offered a further reduced surface roughness.

A Technical Overview of Metallic Parts in Hybrid Additive Manufacturing Industry

Abstract: Additive manufacturing technologies have emerged as the promising alternatives of conventional manufacturing techniques. Conventional manufacturing techniques involves cutting and removal of material by mechanical procedures to achieve final product. Whereas, discrete chunks of material in any form are combined point by point and layer by layer for the fabrication of final product in additive manufacturing processes. Numerous advantages and inefficiencies of these manufacturing techniques are reflected in factors such as the design, fabrication, material properties and working condition etc. Therefore, development of a production technology by combining the benefits of both conventional and additive techniques is significantly important. “Hybrid Manufacturing” jointly apply additive and conventional production methods to attain final products. Hence, this short overview covers the operation aspects of both additive and subtractive manufacturing of metallic materials.