Special Interest Conference : Structured & Freeform Surfaces
Tutorial
Tutorial: Measurement uncertainty for dimensional metrology
Tuesday 10th September 2024
Time: 08:30 – 12:00 (BST)
The tutors are Prof. Samanta Piano, Dr Helia Hooshmand, Dr Xiangjun Kong, Mr Athanasios Pappas, Mr Mingda (Harvey) Yang who are all from the University of Nottingham
This tutorial begins with a one hour lecture on Measurement uncertainty for dimensional metrology by Prof Samanta Piano, followed by 2-Hour Lab Sessions.
Based on the number of participants, we will divide them into two groups. Each group will attend two sessions, each lasting 1 hour.
Session 1: Surface Characterisation (Dr Helia Hooshmand, Mr Thanos Pappas)
The session will begin with a 15-minute overview of the laboratory and the different surface topography measuring instruments available in it. Following the introduction participants will be able to directly interact with the instruments (such as Alicona G5 or Zygo Nexview NX2) and use them to measure different samples. After the conclusion of the measurements, participants will be able to analyse their measurements using the built-in software to determine the areal surface parameters of interest e.g. Sa, Sq.
Session 2: Form Characterisation (Dr Xiangjun Kong, Mr Mingda (Harvey) Yang)
Following a 15-minute overview of form metrology, including photogrammetry and fringe projection profilometry, participants will use one of our form instruments (GOM or Photogrammetry system) to carry out form measurements on a preselected part. For the fringe projection profilometry, stitching of the measurered part will be shown to obtain a complete point cloud, and the measurement results will be evaluated. The photogrammetry session will demonstrate how to capture the images of a manufactured part and import the camera calibration results into Agisoft software to perform a scale-calibrated 3D reconstruction. Using CloudCompare software, the measured part will be compared with its CAD model.
Target Audience: The tutorial is open to everyone, including graduate and postgraduate engineers/physicists, post-doctoral researchers, and scientific managers. A basic knowledge of metrology will be beneficial
This is a beginner to intermediate level course, with material ranging from basic to advanced, to provide both an overview and references for further studies.
Expected Outcomes: Participants will acquire knowledge in surface and form metrology and learn basic operations of various measuring systems. Post-processing analysis will help them identify key parameters for surface and form characterization. Additionally, the lecture will provide a solid understanding of the principle of measurement uncertainty and its importance.
Dr Samanta Piano is Professor of Metrology at the University of Nottingham (UoN), director of the Midlands Centre for Data-Driven Metrology, head of the Advanced Manufacturing Technology Research group, and Associate Head of the Department. With a background as a Marie Curie and UoN Advanced Research Fellow, she has made significant contributions to experimental condensed matter physics, materials science, atomic and optical physics, metrology, and nanotechnology. As head of the Manufacturing Metrology team at UoN her current research focuses on developing innovative optical techniques for high-precision coordinate metrology, leveraging artificial intelligence and quantum technologies to enhance optical measurement systems and promote sustainable manufacturing. Her research excellence is reflected in her publications and invited talks at national and international conferences.
Dr Helia Hooshmand is currently a postdoctoral research fellow at the University of Nottingham. She completed her bachelor’s degree in physics and her master’s degree in condensed matter physics at the University of Tehran, Iran. She then obtained her PhD in experimental optics from Shahid Beheshti University, Iran, in 2020. Her research involves studying the properties of materials using optical techniques such as interferometry, diffractometry, and statistical optics. She joined the Manufacturing and Metrology Team at the University of Nottingham in 2021. Her research interests include the development of optical techniques for surface topography measurement.
Dr. Xiangjun Kong is a research fellow in Metrology at the University of Nottingham (UoN). His PhD research, funded by the China scholarship council (CSC) and Campus France scholarships, focused on optical metrology using structured light profilometry (SLP). He concentrated on designing micro-measurement systems and addressing challenges such as limited depth of field and specular reflections. Currently, he is concentrating on applying machine learning methods to detect defects on surfaces of parts fabricated by laser powder bed fusion (LPBF). Additionally, he is involved in designing fringe projection configurations for implementation in LPBF machines.
Mr Athanasios Pappas is a Research associate in the Manufacturing Metrology Team of the University of Nottingham and serves as the technical officer for the commercial metrology laboratory of the team. His main research areas include surface metrology, measurement uncertainty and surface characterisation. The focus of his PhD research was the metrological characteristics framework and specifically the determination of topography fidelity using a virtual instrument. As the technical officer of the metrology laboratory, he is an expert user of both surface and form metrology instruments
Mr Mingda (Harvey) Yang is a second-year PhD student in the manufacturing Metrology team at the University of Nottingham. His PhD is focused on the development of an intelligent photogrammetric system for optical metrology, by using machine learning techniques for object detection and segmentation, he developed the measurand extraction and background removal method from the chaotic environment of captured images. He is currently developing a trinocular close-range photogrammetric system, in the meantime, he is also involved in measuring the trajectory of industrial robotic arms by a binocular vision system to improve its movement accuracy.