Metrology, Volume 2, Issue 4 (December 2022) – 6 articles

This study proposes an algorithm to autonomously generate the scan path for a laser line scanner mounted on a coordinate measuring machine. The scan path is determined based on task-specific measurement uncertainty in order to prove conformance to specified tolerances. The novelty of the algorithm is the integration of measurement uncertainty. This development is made possible by recent developments for digital twins of optical measurement systems. Furthermore, the algorithm takes all the constraints of this optical measurement system into account. The proposed algorithm is validated on different objects with different surface characteristics. The validation is performed experimentally by a physical measurement system and virtually by an in-house developed digital twin. The validation proves that theoretical coverable areas are measured properly, and the method applied to the equipment used leads to adequate measurement paths that give measurements results with sufficient measurement uncertainty to prove conformance to specifications. Full article

High-accuracy source standards preparation in radionuclide metrology is based on a properly described and reliable weighing procedure able to achieve relative standard uncertainties below 0.1%. However, the results of uncertainty budget comparison CCRI(II)-S7 put in check the ability of the former pycnometer and substitution weighing methods to attain this goal. As a result, a question arises about the validation of mass measurements performed from the elimination weighing method when appropriate uncertainties are required. In order to address this problem, a comprehensive in situ validation methodology is proposed for the results of the pycnometer, substitution, elimination and modified elimination (MEM) methods. Mass comparisons are applied to evaluate the compatibility between weighing methods’ results. It is possible due to a developed weighing sequence, which allows for the performing of all methods by only one drop deposition in the range of mass from 10 mg to 200 mg. As a result, the high degree of compatibility between the MEM and elimination method for uncertainties below 0.1% has been achieved, as well as for higher uncertainties to pycnometer and substitution methods. Numerical simulations indicate that the validation results remain valid on improved technical implementations for these last two methods. Full article

Major aircraft manufacturers are expecting the commercial aircraft market to overcome the pre-COVID levels by 2025, which demands an increase in the production rate. However, aeronautical product assembly processes are still mainly manually performed with a low level of automation. Moreover, the current industry digitalization trend offers the possibility to develop faster, smarter and more flexible manufacturing processes, aiming at a higher production rate and product customization. Here, the integration of metrology within the manufacturing processes offers the possibility to supply reliable data to constantly adjust the assembly process parameters aiming at zero-defect, more digital and a higher level of automation manufacturing processes. In this context, this article introduces the virtual metrology as an assistant of the assembly process of the Advanced Rear-End fuselage component. It describes how the assembly process CADmodel is used by simulation tools to design, set up and perform the virtual commissioning of the new metrology-driven assembly methods, moving from a dedicated tooling approach to a more flexible and reconfigurable metrology-aided design. Preliminary results show that portable metrology solutions are fit-to-purpose even for hardly accessible geometries and fulfil the current accuracy demands. Moreover, the simulation environment ensures a user-friendly assembly process interaction providing further set-up time reduction. Full article

Reverse transcription polymerase chain reaction (RT-PCR) targeting select genes of the SARS-CoV-2 RNA has been the main diagnostic tool in the global response to the COVID-19 pandemic. It took several months after the development of these molecular tests to assess their diagnostic performance in the population. The objective of this study is to demonstrate that it was possible to measure the diagnostic accuracy of the RT-PCR test at an early stage of the pandemic despite the absence of a gold standard. The study design is a secondary analysis of published data on 1014 patients in Wuhan, China, of whom 59.3% tested positive for COVID-19 in RT-PCR tests and 87.6% tested positive in chest computerized tomography (CT) exams. Previously ignored expert opinions in the form of verbal probability classifications of patients with conflicting test results have been utilized here to derive the informative prior distribution of the infected proportion. A Bayesian implementation of the Dawid-Skene model, typically used in the context of crowd-sourced data, was used to reconstruct the sensitivity and specificity of the diagnostic tests without the need for specifying a gold standard. The sensitivity of the RT-PCR diagnostic test developed by China CDC was estimated to be 0.707 (95% Cr I: 0.664, 0.753), while the specificity was 0.861 (95% Cr I: 0.781, 0.956). In contrast, chest CT was found to have high sensitivity (95% Cr I: 0.969, 1.000) but low specificity (95% Cr I: 0.477, 0.742). This estimate is similar to estimates that were found later in studies designed specifically for measuring the diagnostic performance of the RT-PCR test. The developed methods could be applied to assess diagnostic accuracy of new variants of SARS-CoV-2 in the future. Full article

Data-driven manufacturing in Industry 4.0 demands digital metrology not only to drive the in-process quality assurance of manufactured products but also to supply reliable data to constantly adjust the manufacturing process parameters for zero-defect manufacturing processes. Better quality, improved productivity, and increased flexibility of manufacturing processes are obtained by combining intelligent production systems and advanced information technologies where in-process metrology plays a significant role. While traditional coordinate measurement machines offer strengths in performance, accuracy, and precision, they are not the most appropriate in-process measurement solutions when fast, non-contact and fully automated metrology is needed. In this way, non-contact optical 3D metrology tackles these limitations and offers some additional key advantages to deploying fully integrated 3D metrology capability to collect reliable data for their use in intelligent decision-making. However, the full adoption of 3D optical metrology in the manufacturing process depends on the establishment of metrological traceability. Thus, this article presents a practical approach to the task-specific uncertainty assessment realisation of a dense point cloud data type of measurement. Finally, it introduces an experimental exercise in which data-driven 3D point cloud automatic data acquisition and evaluation are performed through a model-based definition measurement strategy. Full article