Investigating the Impact of Process Parameters on Bead Geometry in Laser Wire-Feed Metal Additive Manufacturing DOI Creative Commons
Mohammad Abuabiah,

Tizia Charlotte Weidemann,

Mahdi Amne Elahi

et al.

Journal of Manufacturing and Materials Processing, Journal Year: 2024, Volume and Issue: 8(5), P. 204 - 204

Published: Sept. 19, 2024

Laser wire-feed metal additive manufacturing (LWAM) is an innovative technology that shows many advantages compared with traditional approaches. Despite these advantages, its industrial adoption limited by complex parameter management and inconsistent process quality. To address issues improve geometric accuracy, this study explores how parameters influence bead geometry. We conducted a varying laser power, wire feed rate, traverse speed, welding angle. Using full factorial design central composite methodology, we assessed height width. This allowed us to develop model estimate ideal parameters. The findings offer detailed analysis of interactions their effects on geometry, aiming enhance accuracy stability in LWAM. Moreover, have evaluated the proposed from our developed model, which showed significant enhancement overall was validated via printing single layer multi-layer structures. quality final predicted sample using method improved 40% best produced for Design Experiment trials.

Language: Английский

Microstructures and wear properties of directed energy deposited materials on substrates containing FCCZ structures DOI
Kyoon Choi, Jong-Rae Cho, Do-Sik Shim

et al.

Journal of Manufacturing Processes, Journal Year: 2025, Volume and Issue: 147, P. 70 - 79

Published: May 13, 2025

Language: Английский

Citations

0
Improving the Interpretability of Data-Driven Models for Additive Manufacturing Processes Using Clusterwise Regression DOI Creative Commons
Giulio Mattera,

Gianfranco Piscopo,

Maria Longobardi

et al.

Mathematics, Journal Year: 2024, Volume and Issue: 12(16), P. 2559 - 2559

Published: Aug. 19, 2024

Wire Arc Additive Manufacturing (WAAM) represents a disruptive technology in the field of metal additive manufacturing. Understanding relationship between input factors and layer geometry is crucial for studying process comprehensively developing various industrial applications such as slicing software feedforward controllers. Statistical tools clustering multivariate polynomial regression provide methods exploring influence on final product. These facilitate application development by helping to establish interpretable models that engineers can use grasp underlying physical phenomena without resorting complex models. In this study, an experimental campaign was conducted print steel components using WAAM technology. Advanced statistical were employed mathematical modeling process. The results obtained linear regression, neural network optimized Tree-structured Parzen Estimator (TPE) compared. To enhance performance while maintaining interpretability models, clusterwise introduced alternative technique along with regression. showed proposed approach achieved comparable modeling, Mean Absolute Error (MAE) 0.25 mm height 0.68 width compared 0.23 0.69 network. Notably, preserves models; further discussion topic presented well.

Language: Английский

Citations

2
Effect of laser-wire interaction on bead characteristics at non-planar orientations during off-axis directed energy deposition DOI
Sumitkumar Rathor, Ekta Singla, Ravi Kant

et al.

Progress in Additive Manufacturing, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 12, 2024

Language: Английский

Citations

2
A review of synthesis methods, and characterization techniques of polymer nanocomposites for diverse applications DOI Creative Commons
Shimelis Tamene Gobena,

Abraham Debebe Woldeyonnes

Discover Materials, Journal Year: 2024, Volume and Issue: 4(1)

Published: Oct. 3, 2024

Language: Английский

Citations

2
A model-based approach to reduce kinematics-related overfill in robot-guided Laser Directed Energy Deposition DOI Creative Commons
Avelino Zapata, А. Ф. Бенда, Max Spreitler

et al.

CIRP journal of manufacturing science and technology, Journal Year: 2023, Volume and Issue: 45, P. 200 - 209

Published: July 12, 2023

Laser Directed Energy Deposition is an Additive Manufacturing process, which combines the advantages of a high precision and deposition rate. Nevertheless, geometric quality produced parts compromised by unintentional material accumulation, so-called overfill, at corner sections. This undesired effect results from kinematics system, includes trajectory traverse speed process. By appropriately modeling overfill can be predicted compensated adequately adapting wire speed. Therefore, this work proposes pixel-based model, predicts based on data provided utilized six-axis industrial robot. The presented model experimentally measured single beads with different angles speeds error less than ± 1 mm3. With influence reduction during process was then studied. Furthermore, it shown that according to simulation results, could reduced 2 Finally, effectiveness approach facilitate uniform layer height demonstrated manufacturing multi-layer part, featured 45° 90° contributes towards first-time-right production additively manufactured using processes.

Language: Английский

Citations

6
Application of artificial intelligence in additive manufacturing DOI Open Access

Sungmo Gu,

Min-Hyeok Choi,

Hwijae Park

et al.

JMST Advances, Journal Year: 2023, Volume and Issue: 5(4), P. 93 - 104

Published: Dec. 1, 2023

Language: Английский

Citations

6
Modeling and Control of Layer Height in Laser Wire Additive Manufacturing DOI Open Access
Natago Guilé Mbodj, Mohammad Abuabiah, Peter Plapper

et al.

Materials, Journal Year: 2022, Volume and Issue: 15(13), P. 4479 - 4479

Published: June 25, 2022

Laser Wire Additive Manufacturing (LWAM) is a flexible and fast manufacturing method used to produce variants of high metal geometric complexity. In this work, physics-based model the bead geometry including process parameters material properties was developed for LWAM large-scale products. The aimed include critical parameters, thermal history describe relationship between layer height with different inputs (i.e., power, standoff distance, temperature, wire-feed rate, travel speed). Then, Model Predictive Controller (MPC) designed keep trajectory constant taking into consideration constraints faced in technology. Experimental validation results were performed check accuracy proposed revealed that matches experimental data. Finally, MPC controller able track predefined reference signal by controlling temperature input system.

Language: Английский

Citations

8
Virtual surface morphology generation of Ti-6Al-4V directed energy deposition via conditional generative adversarial network DOI Creative Commons
Taekyeong Kim, Jung Gi Kim, Sangeun Park

et al.

Virtual and Physical Prototyping, Journal Year: 2022, Volume and Issue: 18(1)

Published: Sept. 28, 2022

The core challenge in directed energy deposition is to obtain high surface quality through process optimisation, which directly affects the mechanical properties of fabricated parts. However, for expensive materials like Ti-6Al-4V, cost and time required optimise parameters can be excessive inducing good quality. To mitigate these challenges, we propose a novel method with artificial intelligence generate virtual morphology Ti-6Al-4V parts by given parameters. A high-resolution image generation system has been developed optimising conditional generative adversarial networks. matches experimental cases well an Fréchet inception distance score 174, range accurate matching. Microstructural analysis guidance exhibited less textured microstructural behaviour on reduces anisotropy columnar structure. This help high-quality cost-effectively.

Language: Английский

Citations

8
Development of a Multimaterial Structure Based on CuAl9Mn2 Bronze and Inconel 625 Alloy by Double-Wire-Feed Additive Manufacturing DOI Creative Commons
К. Н. Калашников, Т. А. Калашникова, V. М. Semenchuk

et al.

Metals, Journal Year: 2022, Volume and Issue: 12(12), P. 2048 - 2048

Published: Nov. 28, 2022

This work studied the possibility of producing multimaterials consisting aluminum bronze CuAl9Mn2 and nickel-based superalloy Inconel 625 by double-wire electron beam additive manufacturing. Samples with 5%, 15%, 25%, 50% alloy in were produced for research. The structural features these analyzed, tensile properties, microhardness, dry sliding friction properties measured. results showed that multimaterial composition provides formation a dendritic structure. Such material shows worse values ductility wear resistance. containing 25% provide similar coefficient values, whereas, increasing concentration alloy, material’s ultimate strength microhardness increase significantly.

Language: Английский

Citations

8
On the Microstructure Development under Cyclic Temperature Conditions during WAAM of Microalloyed Steels DOI Creative Commons
Chang Huang, Mohamed Soliman, Kai Treutler

et al.

Metals, Journal Year: 2022, Volume and Issue: 12(11), P. 1913 - 1913

Published: Nov. 8, 2022

This paper shed light on the kinetics of transformation and developed microstructure during wire arc additive manufacturing (WAAM). Three microalloyed alloys, two them are high strength low alloyed steel (HSLA) grades third is a Ni-Cr-Mo steel, from which welding wires being produced, were investigated. Repeated cycles around varied temperatures reheating temperature 1350 °C down to 35 below Ae1 applied using dilatometer samples steels. After applying cycles, dilatometric-samples investigated metallographically their macro- microhardness values measured. It shown that WAAM HSLA steels produce softer structure than wire. Combined microalloying with Ti Nb can present useful strategy for producing finer in components due effect inhibiting prior austenite grain-growth refining final structure. Additionally, repeated heating near Ae3 refines grains produced fine ferrite-pearlite case predominated by granular bainite alloy. The former was softest one steels, whereas alloy tempered martensite Ae1. Idealized curves chosen heat treatment, could be characterized well-defined manner. In future work such idealized together histories obtained WAAM-process will used set up database train an AI-model predicting material properties.

Language: Английский

Citations

7