ASPE-euspen 2020 Summer Topical Meeting – Additive Manufacturing

ASPE-euspen 2020 Summer Topical Meeting – Additive Manufacturing

ASPE-euspen Summer Topical Meeting
Advancing Precision in Additive Manufacturing

Monday July 13 – Friday July 17, 2020: to be modified. 

Due to the current situation with COVID-19, the current travel restrictions on businesses, and our desire to ensure the safety of all, it is with great disappointment that we have decided to cancel the in-person meeting for July 13-17, 2020. Instead, we have chosen to offer a virtual workshop and tutorials. We are planning to hold the virtual workshop and tutorials during that same week. The exact days and times of the event will be announced shortly.

We appreciate your understanding as we all continue to manage this situation and hope that you will continue to support our event at a later date.

John S. Taylor, University of North Carolina at Charlotte
Richard Leach, University of Nottingham, UK

Organizing Committee:
David J. Bate, Nikon Metrology, UK
Marcin B. Bauza, Carl Zeiss Industrial Metrology
Douglas A. Bristow, Missouri University of Science and Technology
Adam Brooks, EWI
Simone Carmignato, University of Padua, Italy
Christopher J. Evans, University of North Carolina at Charlotte
Wim Dewulf, KU Leuven, Belgium
Pete J. Fitsos, Lawrence Livermore National Laboratory
Jason C. Fox, National Institute of Standards and Technology
Brett Griffith, Kansas City National Security Campus
Ola L. A. Harrysson, North Carolina State University
Paul Hooper, Imperial College, UK
Bradley H. Jared, Sandia National Laboratories
Fred van Keulen, Delft University of Technology, Netherlands
Michael M. Kirka, Oak Ridge National Laboratory
Shan Lou, University of Huddersfield, UK
Stephen J. Ludwick, Aerotech, Inc.
David Bue Pedersen, Technical University of Denmark, Denmark
William H. Peter, Oak Ridge National Laboratory
Antonius T. Peijnenburg, VDL Enabling Technologies Group, Netherlands
Senajith Rekawa, Lawrence Berkeley National Laboratory
Johannes Henrich Schleifenbaum, RWTH Aachen University  & Fraunhofer-Institut für Lasertechnik ILT
Tony Schmitz, University of Tennessee, Knoxville
Adam Thompson, University of Nottingham, UK
Ann Witvrouw, KU Leuven, Belgium
Xiayun Zhao, University of Pittsburgh

Call For Papers

Paper Submission Information

Abstract Resources:


  • Dimensional accuracy and surface finish in additive manufacturing (AM)
    • State of the art: What level of precision is achievable?
    • Functional specifications for form and finish
    • Prediction and modeling of dimensional errors and surface topography
    • Developments in fabricating lattice structures with high integrity
    • Diversity in scale of features: large-scale to micro-nano
  • Design for manufacturing
    • Design rules and tolerancing for AM
    • Topology optimization in the context of AM and achieving precision
    • Novel designs for flexures and kinematic couplings
    • Metallurgy and fatigue issues in high-cycle precision applications
  • Characterizing the performance of AM machines
    • In situ process monitoring, e.g. melt zone temperature, powder bed
    • In-process measurement of workpiece shape and topography
    • Using artifacts to assess machine performance; round-robin testing
    • Holistic views of the control system, process feedback, correction
    • Machine learning to conquer the complex AM parameter space
  • Standards
    • Certifying AM equipment capabilities and material properties
    • Industrial demands for ASTM & ISO standards
  • Integrating AM into a holistic manufacturing process
    • Cost-benefit trade-offs of using AM within a complex process chain
    • Engineered partnerships between AM and secondary finishing
    • Kinematic tooling or pallets for repeatable part handling
  • Metrology
    • Surface topography measurements on rough as-built surfaces
    • Dimensional metrology of internal features using computed tomography
    • Multi-sensor approaches, data fusion, and machine learning
    • Complex form measurement, registration, and fitting of point clouds
    • Measurement of 3D lattice strut dimensional accuracy and integrity
    • Characterization of internal defects and voids

Tutorials on July 13th & Tours on July 17th

Short abstracts due: extended to May 4th, 2020

Printable PDF enclosure here

Hotel Accommodations:


Swiss cheese: a practical tutorial on assessing AM build quality
Dr. Paul A. Hooper, Department of Mechanical Engineering, Imperial College, London

Build quality in laser powder bed fusion (LPBF) can seem to vary from excellent to absolutely terrible with the slightest change in processing conditions. A quick and rough way to get some idea of the quality of a build is to check the density of the material. This gives rise to the question: how dense is dense enough? Is it >99% good enough? Or do we need >99.9% or >99.99%? In this tutorial we will take a more detailed look at porosity and outline the limitations of using density alone as a quality metric. We will learn about the concept of a critical flaw and the effect of size and shape on the failure mode of a part. We will then look at simple ways we can determine how likely our part is to contain a critical flaw based on data from a variety sources (e.g. sectioning, X-ray CT or in-situ monitoring). At the end of the tutorial you should be armed with practical ways to assess build quality in LPBF parts.

Bio: Paul Hooper is a Lecturer in the Mechanics of Materials Group in the Department of Mechanical Engineering at Imperial College London. He research focuses on additive manufacturing (AM) and he leads industry-funded projects focusing on certification of AM components. His specific interests include in-situ process monitoring, process-microstructure-performance relationships, simulation of AM processes, design for AM and new process development. He also has interests in high-strain rate material behaviour and structural integrity. He has authored over 30 journal publications, has an h-index of 16 and has one patent.

Measurement uncertainty: the essential minimum
Richard Leach, Manufacturing Metrology Team, Faculty of Engineering, University of Nottingham, UK

In this tutorial, you we learn all that is necessary to be able to assign a quantitative uncertainty with a measurement result. We will cover the following aspects: measurement traceability and terminology, error types, the SI infrastructure, single value uncertainty estimation, measurement with multiple variables, propagation of uncertainty and confidence intervals. Examples will be given from the fields of surface texture measurement and coordinate metrology. The course assumes no prior knowledge of uncertainty estimation and only a basic grasp of mathematics (some basic statistics and partial differentiation of simple functions).


Bio: Professor Richard Leach currently holds the Chair in Metrology in the Faculty of Engineering at the University of Nottingham where he has established The Manufacturing Metrology Team to investigate information-rich metrology of surfaces, to support next-generation manufacturing technologies. Drawing on concepts such as machine learning and sensor fusion, his research is changing the approach to quality control in manufacturing. Prior to his current position, he spent 25 years at the National Physical Laboratory and led a team in surface and nanometrology. He is an internationally recognised researcher in the field of surface topography measurement, particularly in the area of traceability for areal surface metrology, including optical instruments. He has over 480 publications, including 6 textbooks. He is the European Editor-in-Chief for Precision Engineering journal. He is a Fellow of the Institute of Physics, the Institution of Engineering & Technology, the Institute of Measurement & Control, the International Society of Nanomanufacturing, the Higher Education Academy, a Sustained Member of the American Society of Precision Engineering and a Council Member of the European Society of Precision Engineering & Nanotechnology. Richard is a visiting professor at Loughborough University and the Harbin Institute of Technology.

X-ray computed tomography metrology
Adam Thompson, Manufacturing Metrology Team, Faculty of Engineering, University of Nottingham, UK

In this course, we discuss the basics of measurement using X-ray computed tomography (XCT). We will cover the history of and principles behind XCT metrology, including discussion of reconstruction methods and artefacts for calibration. We will examine specific case studies of relevance to dimensional measurement using XCT and review the state of the art in XCT measurement. We will also address some of the issues faced when making XCT measurements and the limitations of the technology, and, finally, cover the specific use of XCT for surface measurement. The aim of this course is to gain a basic understand of measurement using X-ray computed tomography, containing an overview of the theory behind how measurement data is acquired and the factors that affect measurements. The course is aimed at graduate and postgraduate engineers/physicists, post-doctoral researchers and industry technical staff working in measurement using XCT. The course is generally aimed at novice to intermediate XCT users.


Bio: Dr Adam Thompson has been a post-doctoral researcher in the University of Nottingham (UoN) Manufacturing Metrology Team (MMT) since October 2018. Prior to this position, Adam completed his PhD in UoN’s MMT as part of the Centre for Doctoral Training in Additive Manufacture, entitled “Surface texture measurement of metal additively manufactured parts by X-ray computed tomography”, for which he was awarded the Gertrude Cropper Scholarship postgraduate prize by UoN. In his 5 years as an active researcher, Adam has published 12 papers and a book chapter, and presented his work at over 20 international conferences. Adam’s research background is in surface topography measurement of additively manufactured parts, authoring papers on the measurement of metal and polymer parts. Adam also has expertise across metrology, having undertaken postdoctoral projects in performance verification of fringe projection and X-ray computed tomography measurement. Adam also has a deep understanding of co-ordinate and in-process measurement principles, having taught numerous undergraduate and postgraduate courses in basic advanced metrology and performed research activities in the area. Prior to his PhD, Adam taught high school Physics.