scholarly journals Linking In Situ Melt Pool Monitoring to Melt Pool Size Distributions and Internal Flaws in Laser Powder Bed Fusion

Metals ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1856
Author(s):  
Claudia Schwerz ◽  
Lars Nyborg
Keyword(s):  
Near Infrared ◽  
In Situ Monitoring ◽  
Ex Situ ◽  
Process Conditions ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
Melt Pool Size

In situ monitoring of the melt pools in laser powder bed fusion (LPBF) has enabled the elucidation of process phenomena. There has been an increasing interest in also using melt pool monitoring to identify process anomalies and control the quality of the manufactured parts. However, a better understanding of the variability of melt pools and the relation to the incidence of internal flaws are necessary to achieve this goal. This study aims to link distributions of melt pool dimensions to internal flaws and signal characteristics obtained from melt pool monitoring. A process mapping approach is employed in the manufacturing of Hastelloy X, comprising a vast portion of the process space. Ex situ measurements of melt pool dimensions and analysis of internal flaws are correlated to the signal obtained through in situ melt pool monitoring in the visible and near-infrared spectra. It is found that the variability in melt pool dimensions is related to the presence of internal flaws, but scatter in melt pool dimensions is not detectable by the monitoring system employed in this study. The signal intensities are proportional to melt pool dimensions, and the signal is increasingly dynamic following process conditions that increase the generation of spatter.

scholarly journals In-Situ Defect Detection in Laser Powder Bed Fusion by Using Thermography and Optical Tomography—Comparison to Computed Tomography

Metals ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 103 ◽  
Author(s):  
Gunther Mohr ◽  
Simon J. Altenburg ◽  
Alexander Ulbricht ◽  
Philipp Heinrich ◽  
Daniel Baum ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Data Analysis ◽  
Optical Tomography ◽  
In Situ Monitoring ◽  
Process Conditions ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Automatic Data ◽  
Powder Bed

Among additive manufacturing (AM) technologies, the laser powder bed fusion (L-PBF) is one of the most important technologies to produce metallic components. The layer-wise build-up of components and the complex process conditions increase the probability of the occurrence of defects. However, due to the iterative nature of its manufacturing process and in contrast to conventional manufacturing technologies such as casting, L-PBF offers unique opportunities for in-situ monitoring. In this study, two cameras were successfully tested simultaneously as a machine manufacturer independent process monitoring setup: a high-frequency infrared camera and a camera for long time exposure, working in the visible and infrared spectrum and equipped with a near infrared filter. An AISI 316L stainless steel specimen with integrated artificial defects has been monitored during the build. The acquired camera data was compared to data obtained by computed tomography. A promising and easy to use examination method for data analysis was developed and correlations between measured signals and defects were identified. Moreover, sources of possible data misinterpretation were specified. Lastly, attempts for automatic data analysis by data integration are presented.

Vision-based in-situ monitoring system for melt-pool detection in laser powder bed fusion process

2021 ◽  
Vol 68 ◽  
pp. 1735-1745
Author(s):  
Trong-Nhan Le ◽  
Min-Hsun Lee ◽  
Ze-Hong Lin ◽  
Hong-Chuong Tran ◽  
Yu-Lung Lo
Keyword(s):  
Monitoring System ◽  
In Situ Monitoring ◽  
Fusion Process ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool

On the use of spatter signature for in-situ monitoring of Laser Powder Bed Fusion

2017 ◽  
Vol 16 ◽  
pp. 35-48 ◽  
Author(s):  
Giulia Repossini ◽  
Vittorio Laguzza ◽  
Marco Grasso ◽  
Bianca Maria Colosimo
Keyword(s):  
In Situ Monitoring ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed

A Physics-Informed Two-Level Machine Learning Model for Predicting Melt-Pool Size in Laser Powder Bed Fusion

2021 ◽  
Author(s):  
Yong Ren ◽  
Qian Wang ◽  
Panagiotis (Pan) Michaleris
Keyword(s):  
Machine Learning ◽  
Initial Temperature ◽  
Pool Size ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
Input Feature ◽  
Melt Pool Size ◽  
Melt Pool Characteristics

Abstract Laser powder bed fusion (L-PBF) additive manufacturing (AM) is one type of metal-based AM process that is capable of producing high-value complex components with a fine geometric resolution. As melt-pool characteristics such as melt-pool size and dimensions are highly correlated with porosity and defects in the fabricated parts, it is crucial to predict how process parameters would affect the melt-pool size and dimensions during the build process to ensure the build quality. This paper presents a two-level machine learning (ML) model to predict the melt-pool size during the scanning of a multi-track build. To account for the effect of thermal history on melt-pool size, a so-called (pre-scan) initial temperature is predicted at the lower-level of the modeling architecture, and then used as a physics-informed input feature at the upper-level for the prediction of melt-pool size. Simulated data sets generated from the Autodesk's Netfabb Simulation are used for model training and validation. Through numerical simulations, the proposed two-level ML model has demonstrated a high prediction performance and its prediction accuracy improves significantly compared to a naive one-level ML without using the initial temperature as an input feature.

In-Situ Monitoring of Laser Powder Bed Fusion Process Anomalies via a Comprehensive Analysis of Off-Axis Camera Data

2020 ◽  
Author(s):  
Chaitanya Krishna Prasad Vallabh ◽  
Yubo Xiong ◽  
Xiayun Zhao
Keyword(s):  
Real Time ◽  
Network Architecture ◽  
Video Data ◽  
In Situ Monitoring ◽  
Process Efficiency ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Monitoring Method ◽  
Powder Bed

Abstract In-situ monitoring of a Laser Powder-Bed Fusion (LPBF) additive manufacturing process is crucial in enhancing the process efficiency and ensuring the built part integrity. In this work, we present an in-situ monitoring method using an off-axis camera for monitoring layer-wise process anomalies. The in-situ monitoring is performed with a spatial resolution of 512 × 512 pixels, with each pixel representing 250 × 250 μm and a relatively high data acquisition rate of 500 Hz. An experimental study is conducted by using the developed in-situ off-axis method for monitoring the build process for a standard tensile bar. Real-time video data is acquired for each printed layer. Data analytics methods are developed to identify layer-wise anomalies, observe powder bed characteristics, reconstruct 3D part structure, and track the spatter dynamics. A deep neural network architecture is trained using the acquired layer-wise images and tested by images embedded with artificial anomalies. The real-time video data is also used to perform a preliminary spatter analysis along the laser scan path. The developed methodology is aimed to extract as much information as possible from a single set of camera video data. It will provide the AM community with an efficient and capable process monitoring tool for process control and quality assurance while using LPBF to produce high-standard components in industrial (such as, aerospace and biomedical industries) applications.

scholarly journals In situ microstructure analysis of Inconel 625 during laser powder bed fusion

2021 ◽  
Author(s):  
Felix Schmeiser ◽  
Erwin Krohmer ◽  
Christian Wagner ◽  
Norbert Schell ◽  
Eckart Uhlmann ◽  
...  
Keyword(s):  
Laser Power ◽  
Scanning Speed ◽  
High Energy ◽  
Mechanical Anisotropy ◽  
Ex Situ ◽  
Inconel 625 ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed

AbstractLaser powder bed fusion is an additive manufacturing process that employs highly focused laser radiation for selective melting of a metal powder bed. This process entails a complex heat flow and thermal management that results in characteristic, often highly textured microstructures, which lead to mechanical anisotropy. In this study, high-energy X-ray diffraction experiments were carried out to illuminate the formation and evolution of microstructural features during LPBF. The nickel-base alloy Inconel 625 was used for in situ experiments using a custom LPBF system designed for these investigations. The diffraction patterns yielded results regarding texture, lattice defects, recrystallization, and chemical segregation. A combination of high laser power and scanning speed results in a strong preferred crystallographic orientation, while low laser power and scanning speed showed no clear texture. The observation of a constant gauge volume revealed solid-state texture changes without remelting. They were related to in situ recrystallization processes caused by the repeated laser scanning. After recrystallization, the formation and growth of segregations were deduced from an increasing diffraction peak asymmetry and confirmed by ex situ scanning transmission electron microscopy. Graphical Abstract

scholarly journals In Situ Thermography During Laser Powder Bed Fusion of a Nickel Superalloy 625 Artifact with Various Overhangs and Supports

2021 ◽  
Vol 126 ◽  
Author(s):  
Benjamin Molnar ◽  
Jarred C. Heigel ◽  
Eric Whitenton
Keyword(s):  
Cooling Rate ◽  
High Speed ◽  
Nickel Superalloy ◽  
Powder Bed Fusion ◽  
Support Structures ◽  
Radiance Temperature ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool

This document provides details on the experiment and associated measurement files available fordownload in the dataset “In Situ Thermography During Laser Powder Bed Fusion of a Nickel Superalloy 625 Artifact with Various Overhangs and Supports.” The measurements were acquired during the fabrication of a small nickel superalloy 625 (IN625) artifact using a commercial laser powder bed fusion (LPBF) system. The artifact consists of two half-arch features with increasing slopes for overhangs. These overhangs range from 5° from vertical to 85° from vertical in increments of 10°. The artifact geometry and process are controlled to ensure consistent processing along the overhang geometry. This control enables the effect of overhang geometry and support structures to be isolated from effects of inter-layer scan strategy variations. The measurements include high-speed thermography of each layer, from which radiance temperature, cooling rate, and melt pool length are calculated.

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