Brandon M. Lane

Application of Finite Element, Phase-field, and CALPHAD-based Methods to Additive Manufacturing of Ni-based Superalloys

Numerical simulations are used in this work to investigate aspects of microstructure and microseg-regation during rapid solidification of a Ni-based superalloy in a laser powder bed fusion additive manufacturing process. Thermal modeling by finite element analysis simulates the laser melt pool, with surface temperatures in agreement with in situ thermographic measurements on Inconel 625. Geometric and thermal features of the simulated melt pools are extracted and used in subsequent mesoscale simulations. Solidification in the melt pool is simulated on two length scales. For the multicomponent alloy Inconel 625, microsegregation between dendrite arms is calculated using the Scheil-Gulliver solidification model and DICTRA software. Phase-field simulations, using Ni-Nb as a binary analogue to Inconel 625, produced microstructures with primary cellular/dendritic arm spacings in agreement with measured spacings in experimentally observed microstructures and a lesser extent of microsegregation than predicted by DICTRA simulations. The composition profiles are used to compare thermodynamic driving forces for nucleation against experimentally observed precipitates identified by electron and X-ray diffraction analyses. Our analysis lists the precipitates that may form from FCC phase of enriched interdendritic compositions and compares these against experimentally observed phases from 1 h heat treatments at two temperatures: stress relief at 1143 K (870 °C) or homogenization at 1423 K (1150 °C).

Uncertainty of temperature measurements by infrared thermography for metal cutting applications

This paper presents a comprehensive analysis of the uncertainty in the measurement of the peak temperature on the side face of a cutting tool, during the metal cutting process, by infrared thermography. The analysis considers the use of a commercial off-the-shelf camera and optics, typical of what is used in metal cutting research. A physics-based temperature measurement equation is considered and an analytical method is used to propagate the uncertainties associated with measurement variables to determine the overall temperature measurement uncertainty. A Monte Carlo simulation is used to expand on the analytical method by incorporating additional sources of uncertainty such as a point spread function (PSF) of the optics, difference in emissivity of the chip and tool, and motion blur. Further discussion is provided regarding the effect of sub-scenel averaging and magnification on the measured temperature values. It is shown that a typical maximum cutting tool temperature measurement results in an expanded uncertainty of U = 50.1 °C (k = 2). The most significant contributors to this uncertainty are found to be uncertainties in cutting tool emissivity and PSF of the imaging system.

A review on measurement science needs for real-time control of additive manufacturing metal powder bed fusion processes

Additive manufacturing technologies are increasingly used in the development of new products. However, variations in part quality in terms of material properties, dimensional tolerances, surface roughness and defects limit its broader acceptance. Process control today based on heuristics and experimental data yields limited improvement in part quality. In an effort to identify the needed measurement science for real-time closed-loop control of additive manufacturing (AM) processes, this paper presents a literature review on the current AM control schemes, process measurements and modelling and simulation methods as it applies to the powder bed fusion process, though results from other processes are reviewed where applicable. We present our research findings to identify the correlations between process parameters, process signatures and product quality. We also present research recommendations on the key control issues to serve as a technical basis for standards development in this area. Complimentary details to this paper with summary tables, range of values, preliminary correlations and correlation figures can be accessed from a National Institute of Standards and Technology Report (http://nvlpubs.nist.gov/nistpubs/ir/2015/NIST.IR.8036.pdf). This paper is developed based on the report.

Infrared thermography for laser-based powder bed fusion additive manufacturing processes

Additive manufacturing (AM) has the potential to revolutionize discrete part manufacturing, but improvements in processing of metallic materials are necessary before AM will see widespread adoption. A better understanding of AM processes, resulting from physics-based modeling as well as direct process metrology, will form the basis for these improvements. Infrared (IR) thermography of AM processes can provide direct process metrology, as well as data necessary for the verification of physics-based models. We review selected works examining how IR thermography was implemented and used in various powder-bed AM processes. This previous work, as well as significant experience at the National Institute of Standards and Technology in temperature measurement and IR thermography for machining processes, shapes our own research in AM process metrology with IR thermography. We discuss our experimental design, as well as plans for future IR measurements of a laser-based powder bed fusion AM process.

Measurement of the Melt Pool Length During Single Scan Tracks in a Commercial Laser Powder Bed Fusion Process

Contact author: jarred.heigel@nist.gov Certain commercial equipment, instruments, or materials are identified in this paper in order to specify the experimental procedure adequately. Such identification is not intended to imply recommendation or endorsement by the National Institute of Standards and Technology, nor is it intended to imply that the materials or equipment identified are necessarily the best available for the purpose. This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. Approved for public release; distribution is unlimited. ABSTRACT This work presents high speed thermographic measurements of the melt pool length during single track laser scans on nickel alloy 625 substrates. Scans are made using a commercial laser powder bed fusion machine while measurements of the radiation from the surface are made using a high speed (1800 frames per second) infrared camera. The melt pool length measurement is based on the detection of the liquidus-solidus transition that is evident in the temperature profile. Seven different combinations of programmed laser power (49 W to 195 W) and scan speed (200 mm/s to 800 mm/s) are investigated and numerous replications using a variety of scan lengths (4 mm to 12 mm) are performed. Results show that the melt pool length reaches steady state within 2 mm of the start of each scan. Melt pool length increases with laser power, but its relationship with scan speed is less obvious because there is no significant difference between cases performed at the highest laser power of 195 W. Although keyholing appears to affect the anticipated trends in melt pool length, further research is required.

Identifying uncertainty in laser powder bed fusion additive manufacturing models

As additive manufacturing (AM) matures, models are beginning to take a more prominent stage in design and process planning. A limitation frequently encountered in AM models is a lack of indication about their precision and accuracy. Often overlooked, model uncertainty is required for validation of AM models, qualification of AM-produced parts, and uncertainty management. This paper presents a discussion on the origin and propagation of uncertainty in laser powder bed fusion (L-PBF) models. Four sources of uncertainty are identified: modeling assumptions, unknown simulation parameters, numerical approximations, and measurement error in calibration data. Techniques to quantify uncertainty in each source are presented briefly, along with estimation algorithms to diminish prediction uncertainty with the incorporation of online measurements. The methods are illustrated with a case study based on a thermal model designed for melt pool width predictions. Model uncertainty is quantified for single track experiments, and the effect of online estimation in overhanging structures is studied via simulation. [DOI: 10.1115/1.4034103]

Measurement of process dynamics through coaxially aligned high speed near-infrared imaging in laser powder bed fusion additive manufacturing

For process stability in laser powder bed fusion (LPBF) additive manufacturing (AM), control of melt pool dimensions is imperative. In order to control melt pool dimensions in real time, sampling frequencies in excess of 10 kHz may be required, which presents a challenge for many thermal and optical monitoring systems. The National Institute of Standards and Technology (NIST) is currently developing the Additive Manufacturing Metrology Testbed (AMMT), which replicates a metal based laser powder bed fusion AM process while providing open architecture for control, sensing, and calibration sources. The system is outfitted with a coaxially aligned, near-infrared (NIR) high speed melt pool monitoring (MPM) system. Similar monitoring systems are incorporated into LPBF research testbeds, and appearing on commercial machines, but at lower available frame rates, which may limit observation of higher frequency events such as spatter or size fluctuations. This paper presents an investigation of the coaxial imaging systems of the AMMT to capture the process dynamics, and quantify the effects of dynamic fluctuations on melt pool size measurements. Analysis is carried out on a baseline experiment with no powder material added, melt pool size measurements collected in-situ are compared to ex-situ measurements, and results are discussed in terms of temporal bandwidth. Findings will show that, even at the frame rate and resolution presented, challenges in relating in-situ video signals to the ex-situ measurement analysis remain.

Multiple sensor detection of process phenomena in laser powder bed fusion

Laser powder bed fusion (LPBF) is an additive manufacturing (AM) process in which a high power laser melts metal powder layers into complex, three-dimensional shapes. LPBF parts are known to exhibit relatively high residual stresses, anisotropic microstructure, and a variety of defects. To mitigate these issues, in-situ measurements of the melt-pool phenomena may illustrate relationships between part quality and process signatures. However, phenomena such as spatter, plume formation, laser modulation, and melt-pool oscillations may require data acquisition rates exceeding 10 kHz. This hinders use of relatively data-intensive, streaming imaging sensors in a real-time monitoring and feedback control system. Single-point sensors such as photodiodes provide the temporal bandwidth to capture process signatures, while providing little spatial information. This paper presents results from experiments conducted on a commercial LPBF machine which incorporated synchronized, in-situ acquisition of a thermal camera, high-speed visible camera, photodiode, and laser modulation signal during fabrication of a nickel alloy 625 AM part with an overhang geometry. Data from the thermal camera provides temperature information, the visible camera provides observation of spatter, and the photodiode signal provides high temporal bandwidth relative brightness stemming from the melt pool region. In addition, joint-time frequency analysis (JTFA) was performed on the photodiode signal. JTFA results indicate what digital filtering and signal processing are required to highlight particular signatures. Image fusion of the synchronized data obtained over multiple build layers allows visual comparison between the photodiode signal and relating phenomena observed in the imaging detectors.

Optical design and initial results from NIST's AMMT/TEMPS facility

The National Institute of Standards and Technologys (NIST) Physical Measurement and Engineering Laboratories are jointly developing the Additive Manufacturing Measurement Testbed (AMMT)/ Temperature and Emittance of Melts, Powders and Solids (TEMPS) facilities. These facilities will be co-located on an open architecture laser-based powder bed fusion system allowing users full access to the systems operation parameters. This will provide users with access to machine-independent monitoring and control of the powder bed fusion process. In this paper there will be emphasis on the AMMT, which incorporates in-line visible light collection optics for monitoring and feedback control of the powder bed fusion process. We shall present an overview of the AMMT/TEMPS program and its goals. The optical and mechanical design of the open architecture powder-bed fusion system and the AMMT will also be described. In addition, preliminary measurement results from the system along with the current status of the system will be described.NIST’s Physical Measurement and Engineering Laboratories are jointly developing the Additive Manufacturing Measurement Test bed (AMMT)/ Temperature and Emittance of Melts, Powders and Solids (TEMPS) facilities. These facilities will be co-located on an open architecture laser-based powder bed fusion system allowing users full access to the system’s operation parameters. This will provide users with access to machine-independent monitoring and control of the powder bed fusion process. In this paper there will be emphasis on the AMMT, which incorporates in-line visible light collection optics for monitoring and feedback control of the powder bed fusion process. We shall present an overview of the AMMT/TEMPs program and it goals. The optical and mechanical design of the open architecture powder-bed fusion system and the AMMT will be also be described. In addition, preliminary measurement results from the system along with the current system status of the system the will be described.

Identifying uncertainty in Laser Powder Bed Fusion models

A limitation frequently encountered in additive manufacturing (AM) models is a lack of indication about their precision and accuracy. Often overlooked, information on model uncertainty is required for validation of AM models, qualification of AM-produced parts, and uncertainty management. This paper presents a discussion on the origin and propagation of uncertainty in Laser Powder Bed Fusion (L-PBF) models. Four sources of uncertainty are identified: modeling assumptions, unknown simulation parameters, numerical approximations, and measurement error in calibration data. Techniques to quantify uncertainty in each source are presented briefly, along with estimation algorithms to diminish prediction uncertainty with the incorporation of online measurements. The methods are illustrated with a case study based on a transient, stochastic thermal model designed for melt pool width predictions. Model uncertainty is quantified for single track experiments and the effect of online estimation in overhanging structures is studied via simulation. The application of these concepts to estimation and control of the L-PBF process is suggested.© 2016 ASME