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In-situ temperature estimation using machine vision and neural networks in directed energy deposition using a laser beam and wire
University West, Department of Engineering Science, Division of industrial automation. (KAMPT)
2026 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Directed Energy Deposition using a laser beam and metallic wire (directed energy deposition using a laser beam with wire (DED-LB/w)) is a promising additive manufacturing technique known for its high deposition rates, low material waste, and suitability for applications such as the repair of high-value components, rapid prototyping, and low-volume production. As a layered manufacturing process, it builds metal structures by melting and depositing wire in successive beads and layers. While DED-LB/w offers significant advantages, including potential cost and lead time reductions, especially when automated, its complex thermal and geometric dynamics present major challenges for process stability and part quality. Achieving consistent outcomes requires real-time, non-intrusive monitoring solutions capable of capturing critical process parameters, such as the temperature of the deposit, which significantly influences bead geometry, microstructure, and overall mechanical properties.

The setup used in this study consisted of a vision camera and a pyrometer, with the vision camera potentially replaceable by a pyrometer. The proposed measurement approach enables reliable estimation of the immediate solidification temperature and serves as a compact and flexible alternative to conventional pyrometers, which often suffer from a limited field of view and alignment challenges.

This leads to a solution that is industrially practical, low-cost, and robust, and that can be easily installed to existing DED-LB/w systems.   The results revealed the effectiveness of the proposed temperature estimation method, showing strong correlations between the melt pool’s top-surface length and the immediate solidification temperature. Temperature variations (increasing and decreasing, and how fast it reacts to the changes in laser power) during multi-layer deposition can be tracked using in-situ melt pool length measurements. Comparative analysis of the melt pool’s top-surface length and area revealed that melt pool length is a better representative of temperature variations, and it can be used for controlling energy input in multi-layer depositions in DED-LB/w.

In another set of experiments, the influence of preheat temperature on melt pool behavior, melt pool-wire interaction, and microstructure of as-deposited beads was presented, using vision and high-speed cameras and resistive preheating of the feedstock wire. The results of these experiments showed that higher preheat temperatures reduce the thermal gradient between the melt pool and substrate, resulting in larger melt pool volume. Beyond a threshold around 400°C preheat temperature melt pool width showed a gradual increase, larger melt pool volumes resulted in bigger cross-section of liquid bridge and better flow of free electrons from wire to melt pool therefore a jump in electrical conductance values. Higher preheat temperatures shortened and thickened the liquid bridge. A hotter substrate reduces the temperature difference between melt pool and incoming wire, enabling faster and more uniform melting upon contact. The wire reaches melting conditions over a shorter distance while the sustained molten state maintains a thicker transfer region with greater metal flow. The bead cross-section measurements showed a sharp increase in depth and total area of the beads. Microstructural analysis revealed coarser solidification features at higher preheat temperatures caused by reduced cooling rates.

Overall, this work contributes to the advancement of in-situ monitoring in DED-LB/w by demonstrating the feasibility and benefits of vision-based temperature estimation and the suitability of electrical sensing as a feedback variable for closed-loop control of heat input. By quantifying the effects of thermal history and validating predictive models, the study lays the foundation for future development of closed-loop control strategies in wire-based additive manufacturing.

Place, publisher, year, edition, pages
Trollhättan: University West , 2026. , p. 54
Series
Licentiate Thesis: University West ; 58
Keywords [en]
Directed Energy Deposition using a Laser beam and Metallic Wire (DED-LB/w), Temperature Estimation, Machine Vision, Neural Networks
Keywords [sv]
Tillverkning med laser och tråd (DED-LB/w), Temperaturestimering, Maskinseende, Neurala nätverk
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology
Identifiers
URN: urn:nbn:se:hv:diva-24848ISBN: 978-91-89969-62-9 (print)ISBN: 978-91-89969-63-6 (electronic)OAI: oai:DiVA.org:hv-24848DiVA, id: diva2:2039941
Presentation
2026-03-19, F211, Gustava Melins gata, Trollhättan, 13:00 (English)
Opponent
Supervisors
Available from: 2026-03-19 Created: 2026-02-19 Last updated: 2026-03-19
List of papers
1. Correlating melt pool geometry with temperature dynamics in laser directed energy deposition with wire: insights and industrial implications
Open this publication in new window or tab >>Correlating melt pool geometry with temperature dynamics in laser directed energy deposition with wire: insights and industrial implications
2025 (English)In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 140, no 7-8, p. 3869-3882Article in journal (Refereed) Published
Abstract [en]

Directed energy deposition using laser beam and wire feed is a critical technology in high-productivity metal additive manufacturing, enabling precise deposition and fabrication of components with high quality and deposition rates. The interaction between the laser beam and metal is highly temperature-sensitive, affecting metal transfer, melting, solidification, and phase transformations. Effective control of heat input is crucial for influencing the geometry, microstructure, and overall integrity of the fabricated parts.

This study investigates the correlation between the melt pool top surface boundary contour and the immediate solidification temperature, utilizing machine vision and radiation pyrometer measurements. The research highlights the significance of melt pool length as an indicator of temperature variations during deposition. System identification techniques were employed to develop a predictive model of the dynamic relationship between melt pool length and temperature, aimed at enhancing process control strategies. Our approach substitutes off-axis pyrometry with a cost-effective coaxial vision camera integrated into the laser head. By incorporating a vision camera without active illumination, the study offers a compact, omnidirectional solution. Comparative analysis of melt pool length and area measurements demonstrates the superiority of length-based correlations with temperature data.

This work addresses the challenges of heat-input control in directed energy deposition laser beam wire processes and suggests future research directions in various metal alloys, complex geometries, and advanced sensing and automatic control methodologies.

Keywords
Additive manufacturing, Directed energy deposition, Laser beam, DED-LB/w, Melt pool, Machine vision
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-24499 (URN)10.1007/s00170-025-16497-5 (DOI)001572031700001 ()2-s2.0-105016567748 (Scopus ID)
Funder
Vinnova, 202103145Swedish Research Council, 20210094
Note

CC BY 4.0

Funding

Open access funding provided by University West. This work was supported by the project TANDEM (2021–03145), Vinnova under the SMART EUREKA cluster on the advanced manufacturing program. It was also supported by grants from the Swedish Knowledge Foundation, project DEDICATE (20210094), which is gratefully acknowledged.

Available from: 2025-10-29 Created: 2025-10-29 Last updated: 2026-03-25
2. Influence of Substrate Preheating on Processing Dynamics and Microstructure of Alloy 718 Produced by Directed Energy Deposition Using a Laser Beam and Wire
Open this publication in new window or tab >>Influence of Substrate Preheating on Processing Dynamics and Microstructure of Alloy 718 Produced by Directed Energy Deposition Using a Laser Beam and Wire
Show others...
2025 (English)In: Metals, E-ISSN 2075-4701, Vol. 15, no 11, p. 1184-1184Article in journal (Refereed) Published
Abstract [en]

Effective thermal management is essential in metal additive manufacturing to ensure process stability and desirable material properties. Directed energy deposition using a laserbeam and wire (DED-LB/w) enables the production of large, high-performance components but remains sensitive to adverse thermal effects during multilayer deposition due to heat accumulation. While prior studies have investigated interlayer temperature control and substrate preheating in DED modalities, including laser-powder and arc-based systems, the influence of substrate preheating in DED-LB/w has not been thoroughly examined.

This study employs substrate preheating to simulate heat accumulation and assess its effects on melt pool geometry, wire–melt pool interaction, and the microstructural evolution of Alloy 718. Experimental results demonstrate that increased substrate temperatures lead to a gradual expansion of the melt pool, with a notable transition occurring beyond 400 ◦C. Microstructural analysis reveals that elevated preheat temperatures promote coarser secondary dendrite arm spacing and the development of wider columnar grains. Moreover, Nb-rich secondary phases, including the Laves phase, exhibit increased size but relatively unchanged area fractions. Observations from electrical conductance measurements and coaxial visual imaging show that preheat temperature significantly affects the process dynamics and microstructural evolution, providing a basis for advanced process control strategies.

Place, publisher, year, edition, pages
MDPI, 2025
Keywords
directed energy deposition; DED-LB/w; substrate preheating; melt pool; melt pool-wire interaction; Alloy 718; microstructural evolution
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-24497 (URN)10.3390/met15111184 (DOI)001624261400001 ()2-s2.0-105023195545 (Scopus ID)
Funder
Vinnova, 2021-03145Swedish Research Council, 20210094
Note

CC  BY 4.0

Funding: This research was funded by the project TANDEM (2021-03145) Vinnova under the SMARTEUREKA cluster on advanced manufacturing program. It was also supported by grants from theSwedish Knowledge Foundation, project DEDICATE (20210094), which is gratefully acknowledged.

Available from: 2025-10-29 Created: 2025-10-29 Last updated: 2026-02-19
3. In-situ Imaging for Temperature Estimation in Laser Directed Energy Deposition with Wire Feedstock Using a Convolutional Neural Network
Open this publication in new window or tab >>In-situ Imaging for Temperature Estimation in Laser Directed Energy Deposition with Wire Feedstock Using a Convolutional Neural Network
2024 (English)In: New Trends in Signal Processing (NTSP), IEEE, 2024, p. 1-5Conference paper, Published paper (Refereed)
Abstract [en]

Accurate temperature estimation is crucial in metal additive manufacturing ensuring component quality and process efficiency. This study introduces the use of Convolutional Neural Networks (CNNs), namely MobileNet and ResNet, to predict temperatures directly from melt pool images without the need for extensive preprocessing. Through comparative analysis, MobileNet demonstrated superior performance over ResNet, achieving a mean absolute error of 0.0562 and a correlation coefficient of 0.9900. These findings underscore the effectiveness of CNNs in real-time temperature prediction tasks within Laser-Directed Energy Deposition with wire (DED-LB/w), highlighting significant advancements and setting the stage for further technological enhancements.

Place, publisher, year, edition, pages
IEEE, 2024
Keywords
convolutional neural network, machine vision, additive manufacturing, directed energy deposition, laser beam, DED-LB/w, temperature estimation, radiation pyrometry
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology; Production Technology
Identifiers
urn:nbn:se:hv:diva-22749 (URN)10.23919/NTSP61680.2024.10726313 (DOI)001359397200025 ()2-s2.0-85210023656 (Scopus ID)
Conference
2024 New Trends in Signal Processing (NTSP) 16-18 Oct. 2024
Funder
Vinnova, 2021-03145
Note

This research was supported by the project TANDEM (2021-03145) Vinnova under the SMART EUREKA cluster on advance manufacturing program.

Available from: 2024-12-12 Created: 2024-12-12 Last updated: 2026-02-19Bibliographically approved

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Sahraeidolatkhaneh, Atieh

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