Considerations and challenges of qualifying a metal powder bed fusion 3D printing process

2021 ◽  
Author(s):  
Ameen Malkawi ◽  
Satya Ganti ◽  
Zahra Aleid ◽  
Hussain Sharrofna ◽  
Naeem Minhas ◽  
...  
Keyword(s):  
3D Printing ◽  
Metal Powder ◽  
International Standards ◽  
Powder Bed Fusion ◽  
Printing Process ◽  
Powder Bed ◽  
Widespread Adoption ◽  
Methods And Techniques ◽  
Process Qualification

Abstract This paper discusses the considerations taken into account before printing additively manufactured (AM) parts, the challenges faced during the printing process, and the standards, methods, and techniques by which the parts are qualified for use. We discuss the four major categories of AM powder bed fusion (PBF) qualification process namely feedstock qualification, machine and process qualification, material qualification, and part qualification. We discuss what each of these qualification processes entails and provide suggestions where appropriate. In this paper, the activity and direction within the international standards community to help drive the widespread adoption of AM technology in various industries is also discussed.

scholarly journals Carbon Particle In-Situ Alloying of the Case-Hardening Steel 16MnCr5 in Laser Powder Bed Fusion

Metals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 896
Author(s):  
Matthias Schmitt ◽  
Albin Gottwalt ◽  
Jakob Winkler ◽  
Thomas Tobie ◽  
Georg Schlick ◽  
...  
Keyword(s):  
Laser Beam ◽  
Mechanical Strength ◽  
Carbon Content ◽  
Metal Powder ◽  
Case Hardening ◽  
Powder Bed Fusion ◽  
Powder Bed ◽  
Carbon Particles ◽  
Case Hardening Steel

The carbon content of steel affects many of its essential properties, e.g., hardness and mechanical strength. In the powder bed fusion process of metals using a laser beam (PBF-LB/M), usually, pre-alloyed metal powder is solidified layer-by-layer using a laser beam to create parts. A reduction of the carbon content in steels is observed during this process. This study examines adding carbon particles to the metal powder and in situ alloying in the PBF-LB/M process as a countermeasure. Suitable carbon particles are selected and their effect on the particle size distribution and homogeneity of the mixtures is analysed. The workability in PBF-LB is then shown. This is followed by an evaluation of the resulting mechanical properties (hardness and mechanical strength) and microstructure in the as-built state and the state after heat treatment. Furthermore, potential use cases like multi-material or functionally graded parts are discussed.

Toward Metamodels for Composable and Reusable Additive Manufacturing Process Models

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Paul Witherell ◽  
Shaw Feng ◽  
Timothy W. Simpson ◽  
David B. Saint John ◽  
Pan Michaleris ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Metal Powder ◽  
Manufacturing Process ◽  
Process Model ◽  
Model Development ◽  
Process Models ◽  
Powder Bed Fusion ◽  
Powder Bed ◽  
Future Work ◽  
Am Processes

In this paper, we advocate for a more harmonized approach to model development for additive manufacturing (AM) processes, through classification and metamodeling that will support AM process model composability, reusability, and integration. We review several types of AM process models and use the direct metal powder bed fusion AM process to provide illustrative examples of the proposed classification and metamodel approach. We describe how a coordinated approach can be used to extend modeling capabilities by promoting model composability. As part of future work, a framework is envisioned to realize a more coherent strategy for model development and deployment.

Fast prediction of thermal distortion in metal powder bed fusion additive manufacturing: Part 1, a thermal circuit network model

2018 ◽  
Vol 22 ◽  
pp. 852-868 ◽  
Author(s):  
Hao Peng ◽  
Morteza Ghasri-Khouzani ◽  
Shan Gong ◽  
Ross Attardo ◽  
Pierre Ostiguy ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Metal Powder ◽  
Network Model ◽  
Thermal Distortion ◽  
Powder Bed Fusion ◽  
Powder Bed ◽  
Thermal Circuit ◽  
Fast Prediction

scholarly journals Synergistic application of continuous granulation and selective laser sintering 3D printing for the development of pharmaceutical dosage forms with enhanced dissolution rates and physical properties

2021 ◽  
Author(s):  
Rishi Thakkar ◽  
Yu Zhang ◽  
Jiaxiang Zhang ◽  
Mohammed Maniruzzaman
Keyword(s):  
Solid State ◽  
3D Printing ◽  
Physical Properties ◽  
Dosage Forms ◽  
Flow Properties ◽  
Printing Process ◽  
Powder Bed ◽  
Printing Processes ◽  
Binder Jetting ◽  
Physical Mixtures

AbstractThis study demonstrated the first case of combining novel continuous granulation with powder-based pharmaceutical 3-dimensional (3D) printing processes to enhance the dissolution rate and physical properties of a poorly water-soluble drug. Powder bed fusion (PBF) and binder jetting 3D printing processes have gained much attention in pharmaceutical dosage form manufacturing in recent times. Although powder bed-based 3D printing platforms have been known to face printing and uniformity problems due to the inherent poor flow properties of the pharmaceutical physical mixtures (feedstock). Moreover, techniques such as binder jetting currently do not provide any solubility benefits to active pharmaceutical ingredients (APIs) with poor aqueous solubility (>40% of marketed drugs). For this study, a hot-melt extrusion-based versatile granulation process equipped with UV-Vis process analytical technology (PAT) tools for the in-line monitoring of critical quality attributes (i.e., solid-state) of indomethacin was developed. The collected granules with enhanced flow properties were mixed with vinylpyrrolidone-vinyl acetate copolymer and a conductive excipient for efficient sintering. These mixtures were further characterized for their bulk properties observing an excellent flow and later subjected to a PBF-3D printing process. The physical mixtures, processed granules, and printed tablets were characterized using conventional as well as advanced solid-state characterization. These characterizations revealed the amorphous nature of the drug in the processed granules and printed tablets. Further, the in vitro release testing of the tablets with produced granules as a reference standard depicted a notable solubility advantage (100% drug released in 5 minutes at >pH 6.8) over the pure drug and the physical mixture. Our developed system known as DosePlus combines innovative continuous granulation and PBF-3D printing process which can potentially improve the physical properties of the bulk drug and formulations in comparison to when used in isolation. This process can further find application in continuous manufacturing of granules and additive manufacturing of pharmaceuticals to produce dosage forms with excellent uniformity and solubility advantage.Abstract Figure

Quality assurance in metal powder bed fusion via deep-learning-based image classification

2019 ◽  
Vol 26 (2) ◽  
pp. 259-266 ◽  
Author(s):  
Maximilian Hugo Kunkel ◽  
Andreas Gebhardt ◽  
Khumbulani Mpofu ◽  
Stephan Kallweit
Keyword(s):  
Machine Learning ◽  
Mechanical Properties ◽  
Quality Control ◽  
Metal Powder ◽  
Monitoring Data ◽  
Powder Bed Fusion ◽  
Destructive Testing ◽  
Deep Convolutional Neural Networks ◽  
Content Type ◽  
Powder Bed

Purpose This paper aims to establish a standardized, quick, reliable and cost-efficient method of quality control (QC) in metal powder bed fusion (PBFM) based on process monitoring data. Design/methodology/approach Based on destructive testing results that emerged from a statistical investigation on powder bed fusion process exceeding reproducibility of mechanical properties, it was investigated if the generated monitoring data from a concept laser machine allows reliable deductions on resulting mechanical properties of the manufactured specimens. Findings The application of machine learning on generated melt pool images, under-recognition of destructive testing results, enables enhanced pattern recognition. The generated computational model successfully classified 9,280 unseen layer images by 98.9 per cent accuracy. This finding offers an automated approach to quality control within PBFM. Originality/value To the authors knowledge, it is the first time that machine learning has been applied for the purpose of QC in additive manufacturing. The ability of deep convolutional neural networks to recognize patterns, which are imperceptible to the human eye, shows high potential to facilitate activities of QC and to minimize QC-related costs and throughput times. The achieved processing speed for image analyses also points a way for future developments of self-corrective PBFM systems.

Area melting with multi-laser arrays to increase build rate for metal powder bed fusion additive manufacturing

2019 ◽  
Author(s):  
Jason H. Karp ◽  
Victor Ostroverkhov ◽  
David Bogdan ◽  
Michael Graham ◽  
Brian Mccarthy ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Metal Powder ◽  
Powder Bed Fusion ◽  
Laser Arrays ◽  
Powder Bed

Microstructure of Built Part Obtained by Powder Bed Fusion Process with Metal

2019 ◽  
Vol 825 ◽  
pp. 1-6
Author(s):  
Tatsuaki Furumoto ◽  
Kyota Egashira ◽  
Souta Matsuura ◽  
Makoto Nikawa ◽  
Masato Okada ◽  
...  
Keyword(s):  
Heat Treatment ◽  
Metal Powder ◽  
Maraging Steel ◽  
Process Parameters ◽  
Steel Powder ◽  
Powder Bed Fusion ◽  
Laser Melting ◽  
Powder Bed ◽  
Suitable Heat Treatment ◽  
Deposited Metal

The influence of various process parameters on the building of maraging steel powder by the selective laser melting (SLM) processes is investigated. The microstructure in the built part was observed and the influence of the heat treatment was evaluated. As results, the depth of solidified layer was higher than that of deposited metal powder, and its value was influenced with the process parameters. The microstructure in the boundary between the built part and the substrate was quite different from the built part even if the suitable heat treatment was performed.

scholarly journals Material Reuse in Laser Powder Bed Fusion: Side Effects of the Laser—Metal Powder Interaction

Metals ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 341 ◽  
Author(s):  
Eleonora Santecchia ◽  
Stefano Spigarelli ◽  
Marcello Cabibbo
Keyword(s):  
Additive Manufacturing ◽  
Side Effects ◽  
Metal Powder ◽  
Three Dimensional ◽  
High Energy ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Metal Additive Manufacturing ◽  
Metal Additive

Metal additive manufacturing is changing the way in which engineers and designers model the production of three-dimensional (3D) objects, with rapid growth seen in recent years. Laser powder bed fusion (LPBF) is the most used metal additive manufacturing technique, and it is based on the efficient interaction between a high-energy laser and a metal powder feedstock. To make LPBF more cost-efficient and environmentally friendly, it is of paramount importance to recycle (reuse) the unfused powder from a build job. However, since the laser–powder interaction involves complex physics phenomena and generates by-products which might affect the integrity of the feedstock and the final build part, a better understanding of the overall process should be attained. The present review paper is focused on the clarification of the interaction between laser and metal powder, with a strong focus on its side effects.

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