Online Melt Pool Depth Estimation During Directed Energy Deposition Using Coaxial Infrared Camera, Laser Line Scanner, and Artificial Neural Network

2021 ◽  
pp. 102295
Author(s):  
Ikgeun Jeon ◽  
Liu Yang ◽  
Kwangnam Ryu ◽  
Hoon Sohn
2021 ◽  
Vol 63 (1) ◽  
pp. 41-47
Author(s):  
Angelina Marko ◽  
Andreas Schafner ◽  
Julius Raute ◽  
Michael Rethmeier

Abstract Additive manufacturing, and therefore directed energy deposition, is gaining more and more interest from industrial users. However, quality assurance for the components produced is still a challenge. Machine learning, especially using artificial neuronal networks, is a potential method for ensuring a high-quality standard. Based on process parameters and monitoring data, part quality can be predicted. A further advantage is the ability to constantly learn and adopt to slight process changes. First tests using artificial neural networks focus on the prediction of track geometry. The results show that even a small data set is enough to provide high accuracy in the predictions. In this work, an artificial neural network for the predictive analysis of relative density in laser powder cladding has been developed. A central composite experimental design is used to generate 19 data sets. Input variables are laser power, feed rate and powder mass flow. Cubes are built up where density is considered as a target value. Several neural networks are trained and evaluated with these data sets. Different topologies and initial weights are considered. The best network reaches a confidence level of around 90 % for the prediction of relative density based on the process parameters. Finally, the optimization of the generalization performance is investigated. To this purpose, methods of variation in error limit as well as cross-validation are applied. In this way, density is predictable by an artificial neural network with an accuracy of about 95 %.


Metals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 634
Author(s):  
Agnieszka Kisielewicz ◽  
Karthikeyan Thalavai Pandian ◽  
Daniel Sthen ◽  
Petter Hagqvist ◽  
Maria Asuncion Valiente Bermejo ◽  
...  

This study investigates the influence of resistive pre-heating of the feedstock wire (here called hot-wire) on the stability of laser-directed energy deposition of Duplex stainless steel. Data acquired online during depositions as well as metallographic investigations revealed the process characteristic and its stability window. The online data, such as electrical signals in the pre-heating circuit and images captured from side-view of the process interaction zone gave insight on the metal transfer between the molten wire and the melt pool. The results show that the characteristics of the process, like laser-wire and wire-melt pool interaction, vary depending on the level of the wire pre-heating. In addition, application of two independent energy sources, laser beam and electrical power, allows fine-tuning of the heat input and increases penetration depth, with little influence on the height and width of the beads. This allows for better process stability as well as elimination of lack of fusion defects. Electrical signals measured in the hot-wire circuit indicate the process stability such that the resistive pre-heating can be used for in-process monitoring. The conclusion is that the resistive pre-heating gives additional means for controlling the stability and the heat input of the laser-directed energy deposition.


2021 ◽  
Vol 53 ◽  
pp. 576-584
Author(s):  
Kandice S.B. Ribeiro ◽  
Henrique H.L. Núñez ◽  
Jason B. Jones ◽  
Peter Coates ◽  
Reginaldo T. Coelho

2021 ◽  
Vol 53 ◽  
pp. 407-416
Author(s):  
Chaitanya Vundru ◽  
Ramesh Singh ◽  
Wenyi Yan ◽  
Shyamprasad Karagadde

Author(s):  
Basil Paudel ◽  
Garrett Marshall ◽  
Scott M. Thompson

Abstract The effects of Ti-6Al-4V part size on its temperature distribution during the blown-powder directed energy deposition (DED) process was investigated through dual-thermographic monitoring and a unique modeling technique. Results demonstrate that the duration of dwell times presented to be a significant contributing factor affecting the rate at which a steady-state temperature field is achieved. As a result, the longer wall took significantly more layers/time to achieve a uniform temperature profile within the wall. Maximum and average melt pool temperatures appear to be near independent of part size at a steady state. Finite element simulation results showed that a quasi-steady melt pool temperature may be unique to a layer, especially during earlier cladding process near the substrate and that the layer-wise steady melt pool was achieved within the first few seconds of track scanning. A proposed fin modeling-based temperature distribution was found to predict the thermal profile in a ‘substrate affected zone’ (SAZ) along the scan direction within 5%. A method to predict the onset of the SAZ has also been proposed. Process parameters used for the DED of component volumes are not necessarily optimal for thin-walled structures due to significantly less thermal capacity.


2019 ◽  
Vol 62 (4) ◽  
pp. 213-217 ◽  
Author(s):  
Abdollah Saboori ◽  
Sara Biamino ◽  
Mariangela Lombardi ◽  
Simona Tusacciu ◽  
Mattia Busatto ◽  
...  

2020 ◽  
Vol 143 (5) ◽  
Author(s):  
Fuda Ning ◽  
Dayue Jiang ◽  
Zhichao Liu ◽  
Hui Wang ◽  
Weilong Cong

Abstract Ultrasonic vibration-assisted (UV-A) directed energy deposition (DED) has become a promising technology to improve the as-built quality and mechanical performance of metal parts. Ultrasonic frequency, a critical parameter of the ultrasonic vibration, can remarkably affect the ultrasonic vibration behaviors in assisting DED processes. However, leveraging varied ultrasonic frequencies in UV-A DED attracts little attention, and the effects of ultrasonic frequency have been thus overlooked. Linking ultrasonic frequency and part performance emphasizes the need for an understanding of the underlying thermodynamics in the melt pool due to the key role of thermal history in the DED process. In this work, we fabricated Inconel 718 (IN718) parts using the UV-A DED process under different levels of ultrasonic vibration frequency (including 0, 25 kHz, 33 kHz, and 41 kHz). For the first time, melt pool size, temperature distribution, and peak temperature within the melt pool, as well as the peak temperature fluctuation within a layer deposition, were studied. Porosity and thermal-dependent properties including grain size and microhardness were also investigated. The results indicated that the increase in ultrasonic frequency led to an increase in both melt pool size and peak temperature. Moreover, the lowest porosity was obtained at an ultrasonic frequency of 25 kHz, while grain refinement and microhardness enhancement were achieved at the highest frequency of 41 kHz. This investigation provides great insights into the link among ultrasonic frequency, melt pool formation, temperature field, porosity, and thermal-dependent properties in the UV-A DED-built IN718 parts.


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