Development of a hybrid method for uncertainty evaluation to provide traceability to dimensional measurements based on X-ray tomography

• Grant number: 18/24757-7
• Support type: Scholarships abroad - Research
• Effective date (Start): December 16, 2019
• Effective date (End): August 31, 2020
• Field of knowledge: Engineering - Mechanical Engineering - Manufacturing Processes
• Principal researcher: Crhistian Raffaelo Baldo
• Grantee: Crhistian Raffaelo Baldo
• Host: Wim Dewulf
• Home Institution: Centro de Engenharia, Modelagem e Ciências Sociais Aplicadas (CECS). Universidade Federal do ABC (UFABC). Ministério da Educação (Brasil). Santo André , SP, Brazil
• Research place: University of Leuven (KU Leuven), Belgium

Abstract

Industrial Computed Tomography (CT) has been part of dimensional quality control loop for more than a decade. In general, complex-shaped parts with hundreds (or even thousands) of features (hidden features as well) can be holistically checked with great operational advantages over other existing coordinate metrology technologies, such as tactile and/or optical coordinate measuring machines. Nevertheless, due to the complex measurement-error cause system, establishing traceability to the quantity intended to be measured with computed tomography has been a key metrology challenge. This research project proposes developing the foundations for a hybrid approach to assessing the task-specific measurement uncertainty based on CT data, based on computational simulations. The proposed hybrid approach considers blending methods in order to reduce both analytical model complexity and Monte Carlo computational load by exploiting properties of different uncertainty contributors. Modeling of uncertainty propagation will therefore differ as a function of the character of the uncertainty contributors, requiring a deep investigation of the physical factors of the X-rays and the geometrical and physical factors of the CT-based measuring system itself. (AU)