Dr Joy Gockel
Colorado School of Mines, US
Surface formation and measurement toward additive manufacturing fatigue properties prediction
Metal additive manufacturing (AM) for critical applications requires a comprehensive understanding of the fatigue failure mechanisms. However, whether to classify process induced flaws as critical defects is currently uncertain. Rough as-printed surfaces in laser powder bed fusion are a particularly dominating mechanism of fatigue failure. In addition to roughness from the layered build process, adhered powder, spatter particles, and other features may be present on the as-built surface. Some of these may not influence the mechanical performance of components but will influence the roughness metrics. The measurement technique used will also impact the calculated metrics and any correlations to mechanical performance. The relationships connecting the contour processing parameters, surface formation and measurement metrics to fatigue life will be discussed. Understanding the influences of surface condition on fatigue behaviour can provide guidance for post-processing requirements and necessary design guidelines around critical defects.
Dr Joy Gockel is an Associate Professor in Mechanical Engineering at Colorado School of Mines, and the Executive Director of the Alliance for the Development of Additive Processing Technology (ADAPT) research center and industry consortium. Joy joined Mines from Wright State University where she was an Assistant Professor in Mechanical and Materials Engineering. Prior to her faculty positions, she was a Lead Engineer at GE Aviation’s Additive Technology Center and earned her PhD in from Carnegie Mellon University. Her work specializes in connecting the additive manufacturing processing-structure-properties-performance relationships. For her research and professional contributions, she has been recognized as a 2020 ASTM International Young Professional in Additive Manufacturing, a 2021 TMS Young Leader, the 2021 International Outstanding Young Researcher in Freeform and Additive Manufacturing (FAME Jr.) and is part of the 2022 class of America Makes Ambassadors.
3D Systems, BE
Manufacturing precision parts with complex geometries using metal LPBF
Making precision components efficiently requires control of the entire manufacturing flow of a part. This presentation gives insight into challenges and best practices when aiming to make precision parts in a reproducible way. Multiple steps in the production process will be covered, including Part Design, Additive Manufacturing, Heat Treatment, Manual Finishing, CNC Machining and Quality Control. Examples used are sourced mainly from the semiconductor industry where high precision meets large quantities.
Niels Holmstock is a mechanical engineer working as Application Development manager for 3D Systems on metal additive manufacturing (AM) applications in their Application Innovation Group (AIG).
Over 7 years of working on complex metal AM projects for the semiconductor industry has taught him how to have both technical and economic success with making complex precision parts. Niels leverages this knowledge daily to accelerate metal AM away from prototyping only and towards a sustainable production technology.
Dr Ian Laidler
Wayland Additive, UK
Neubeam Electron Beam PBF and the advantages of active charge neutralisation
This talk will introduce the concepts of active charge neutralisation and then explore the benefits this brings to the electron beam powder bed fusion process.
Dr Ian Laidler is a Physicist and Engineer with more than 30 years of industrial experience directing complex technical developments of high value capital equipment for the semiconductor and medical industries. Ian has always worked with particle accelerators of some form ranging from superconducting electron synchrotrons for the X-ray lithography programmes of the ‘90s; superconducting proton cyclotrons for PET scanners; X-ray beamlines for the world’s third generation synchrotrons; and electron beam lithography systems for the semiconductor and nanotechnology industries. As a co-founder of Wayland Additive, Ian has brought this experience to the field of electron beam metal AM.
Dr Michele Pavan
Assessing part quality at different stages of the AM workflow
In this presentation we will show how: simulation, process monitoring and control, and analysis of optical images can be used to detect, and potentially correct, common problems occurring in Metal LPBF processes. Using a wide range of examples, we will illustrate how to assess the part quality at different stages of the workflow, improving the robustness of the production chain and decreasing lead times. The insights provided by the presented tools are validated by mean of X-Ray Computed Tomography.
Dr Michele Pavan is a Materials Engineer with an experience of 10 years in different aspects of Additive Manufacturing, ranging from Process Engineering, Quality Control using X-ray Computed Tomography and software development for AM. He currently works as Research Engineering Manager within the Central Research and Technology Unit at Materialise. He holds a PhD in Engineering Technology from KU Leuven and, Master and Bachelor in Materials Engineering from the University of Padua.
Prof. Matthijs Langelaar
Delft University of Technology, NL
Topology Optimization for Additive Manufacturing – Focus on Precision
The past decade has seen rapid advances in both Additive Manufacturing (AM) technologies and computational design methods for AM, most notably Topology Optimization (TO). The design freedom offered by AM and the systematic form-follows-function process of TO form a synergetic combination that enables the generation of designs with unprecedented performance. In this contribution, next to a general introduction to TO-for-AM, recent developments in this field are considered, with special attention to various aspects of precision. This includes design resolution, distortion reduction, AM-enabled precision positioning applications, and also precision regarding material properties of printed parts.
Matthijs Langelaar is Professor at Delft University of Technology, leading the Computational Design and Mechanics research group. The focus of his research is to advance computational design techniques in particular for demanding high-tech applications, with a specific emphasis on topology optimization and design for (additive) manufacturing.
He holds a PhD degree from Delft University of Technology and an MSc degree in Mechanical Engineering from University of Twente. He has also worked at the German Aerospace Center, University of Freiburg in Germany, University of Colorado at Boulder, US, and at Seoul National University, Korea.
Dr Ho Yeung
National Institute of Standards and Technology, US
Voxel level laser control for the laser powder bed fusion process
The laser powder bed fusion (LPBF) process is a widely utilized metal additive manufacturing (AM) technique, known for its capability to generate complex structures, optimized geometries, lightweight components, and intricate designs. Although AM is commonly perceived as a layer-by-layer method, LPBF actually builds parts voxel-by-voxel using a point laser heating source. Consequently, managing the LPBF process at the voxel level—emphasizing each three-dimensional printing element—yields significant benefits. This research presents a novel voxel-level laser control approach, utilizing time-stepped digital commands to coordinate laser power and diameter for each point along the digitally interpolated scan path. This method facilitates model-based scan strategy execution and digital twin-based real-time process control, while providing a clear description of the laser scan strategy, ensuring platform independence. An open-platform testbed, designed around the time-stepped digital command approach, is introduced, and case studies demonstrating various advanced scan strategies employing voxel-level laser control are explored.
Dr Ho Yeung is an Electronics Engineer at the National Institute of Standards and Technology (NIST). His research career began with large plastic deformation, and machine tool control before transitioning to additive manufacturing in recent years. He leads the Machine and Process Control Methods for Additive Manufacturing project at NIST, and developed the AM control system for NIST Additive Manufacturing Metrology Testbed (AMMT). Ho Yeung holds a Ph.D. in Industrial Engineering from Purdue University, where he also earned both his MS and BS in Computer and Electrical Engineering.