Search Results (41)

In the course of digitalization, the importance of modeling and simulating real-world processes in a computer is rapidly increasing. Simulations are now in everyday use in many areas. For example, simulations are used to gain a better understanding of the real experiment, to plan new experiments, or to analyze existing experiments. Simulations are now also increasingly being used as an essential component of a real measurement, usually as part of an inverse problem. To ensure confidence in the results of such virtual measurements, traceability and methods for evaluating uncertainty are needed. In this paper, the challenges and benefits inherent to virtual metrology techniques are shown using three examples from different metrological fields: the virtual coordinate measuring machine, the tilted-wave interferometer, and the virtual flow meter. Full article

In recent years, the semiconductor industry has embraced advanced artificial intelligence (AI) techniques to facilitate intelligent manufacturing throughout their organizations, with particular emphasis on virtual metrology (VM) systems. Nonetheless, the practical application of data-driven virtual metrology for product quality inspection encounters notable hurdles, such as annotating inspections in highly dynamic industrial environments. This leads to complexities and significant expenses in data acquisition and VM model training. To address the challenges, we delved into transfer learning (TL). TL offers a valuable avenue for knowledge sharing and scaling AI models across various processes and factories. At the same time, research on transfer learning in VM systems remains limited. We propose a novel parameter transfer learning (PTL) architecture for VM systems and examine its application in industrial process automation. We implemented cross-factory and cross-recipe transfer learning to enhance VM performance and offer practical advice on adapting TL to meet individual needs and use cases. By leveraging extensive data from Seagate wafer factories, known for their large-scale and high-dimensional nature, we achieved significant PTL performance improvements across multiple performance metrics, with the true positive rate (TPR) increasing by 29% and false positive rate (FPR) decreasing by 43% in the cross-factory study. In contrast, in the cross-recipe study, TPR increased by 27.3% and FPR decreased by 6.5%. With our proposed PTL architecture and its performance achievements, insufficient data from the new manufacturing sites, new production lines and new products are addressed with shorter VM model training time and smaller computational power with strong final quality prediction confidence. Full article

Augmented reality display performance depends strongly on features of the human visual system. This is especially true for retinal scan glasses, which use laser beam scanning and transparent holographic optical combiners. Human-centered approaches allow us to go beyond conventional optical metrology and evaluate display performance as it is perceived in actual augmented reality use cases. Here, we first present a theoretical formula for the retinal scan luminance and ambient contrast ratio calculated from optical powers, wavelengths, field of view, and human pupil diameter. As a promising insight, we found that the pupil diameter dependence is beneficial in assimilating the virtual image luminance to the ambient luminance. Second, we designed and performed a psychophysical experiment to assess perceived resolution in augmented reality settings using a fully functional retinal scan glasses prototype. We present the results of the trials and illustrate how this approach can be used in the further development of augmented reality smart glasses. Full article

This study presents the challenges arising during the numerical design and simulation of surface-microtextured piston rings. The evaluation of performance is based on the values of asperity and hydrodynamic friction, as well as the lubricant film thickness. The simulation tool AVL Excite Piston & Rings is used to perform the calculations. The aim of this study is to understand how selected surface pre-processing (pre-treatment) steps affect the calculations. Two methods are presented to achieve a realistic surface topography representative of a state after running-in. Pre-treatment is performed through metrological filtering and thresholding of the topography, and Gaussian smoothing of the virtually applied micro-texture array is carried out. The results show the anticipated behavior of decreasing asperity and hydrodynamic friction losses with the concurrent application of both techniques. Full article

Virtual experiments are a digital representation of a real measurement and play a crucial role in modern measurement sciences and metrology. Beyond their common usage as a modeling and validation tool, a virtual experiment may also be employed to perform a parameter sensitivity analysis or to carry out a measurement uncertainty evaluation. For the latter to be compliant with statistical principles and metrological guidelines, the procedure to obtain an estimate and a corresponding measurement uncertainty requires careful consideration. We employ a Monte Carlo sampling procedure using a virtual experiment that allows one to perform a measurement uncertainty evaluation according to the Monte Carlo approach of JCGM-101 and JCGM-102, two widely applied guidelines for uncertainty evaluation in metrology. We extend and formalize a previously published approach for simple additive models to account for a large class of non-linear virtual experiments and measurement models for multidimensionality of the data and output quantities, and for the case of unknown variance of repeated measurements. With the algorithm developed here, a simple procedure for the evaluation of measurement uncertainty is provided that may be applied in various applications that admit a certain structure for their virtual experiment. Moreover, the measurement model commonly employed for uncertainty evaluation according to JCGM-101 and JCGM-102 is not required for this algorithm, and only evaluations of the virtual experiment are performed to obtain an estimate and an associated uncertainty of the measurand. We demonstrate the efficacy of the developed approach and the effect of the underlying assumptions for a generic polynomial regression example and an example of a simplified coordinate measuring machine and its virtual representation. The results of this work highlight that considerable effort, diligence, and statistical considerations need to be invested to make use of a virtual experiment for uncertainty evaluation in a way that ensures equivalence with the accepted guidelines. Full article

Virtual experiments (VEs) and digital twins (DTs), pivotal for realizing European strategic policies on sustainability and digitalization within Industry 4.0 and the European Green Deal, simulate physical systems and characteristics in a virtual environment, with DTs incorporating dynamic inputs from and outputs to the real-world counterpart. To ensure confidence in their use and outcomes, traceability and methods to evaluate measurement uncertainty are needed, topics that are hardly covered by the literature so far. This paper provides a harmonized definition of VEs and DTs and introduces a framework for evaluating measurement uncertainty. Furthermore, it discusses how to propagate the uncertainty of the contributions coming from the different parts of the DT. For the core part of the DT, the framework derived for VEs can be used. For the physical-to-virtual (P2V) connection and the virtual-to-physical (V2P) connection, additional sources of uncertainty need to be considered. This paper provides a metrological framework for taking all these uncertainty contributions into account while describing a framework to establish traceability for DTs. Two case studies are presented to demonstrate the proposed methodology considering industrially relevant measuring instruments and devices, namely, a coordinate measuring machine (CMM) and a collaborative robot arm (cobot). Full article

Thanks to the recent development of innovative instruments and software with high accuracy and resolution, 3D modelling provides useful insights in several sectors (from industrial metrology to cultural heritage). Moreover, the 3D reconstruction of objects of artistic interest is becoming mandatory, not only because of the risks to which works of art are increasingly exposed (e.g., wars and climatic disasters) but also because of the leading role that the virtual fruition of art is taking. In this work, we compared the performance of four 3D instruments based on different working principles and techniques (laser micro-profilometry, structured-light topography and the phase-shifting method) by measuring four samples of different sizes, dimensions and surface characteristics. We aimed to assess the capabilities and limitations of these instruments to verify their accuracy and the technical specifications given in the suppliers’ data sheets. To this end, we calculated the point densities and extracted several profiles from the models to evaluate both their lateral (XY) and axial (Z) resolution. A comparison between the nominal resolution values and those calculated on samples representative of cultural artefacts was used to predict the performance of the instruments in real case studies. Overall, the purpose of this comparison is to provide a quantitative assessment of the performance of the instruments that allows for their correct application to works of art according to their specific characteristics. Full article

This paper deals with a metrological and qualitative evaluation of the Artec 3D structured-light scanners: Micro and Space Spider. As part of a larger European project called ITSERR, these scanners are tested to reconstruct small archaeological artefacts, in particular cuneiform tablets with different dimensions. For this reason, Micro and Space Spider are compared in terms of the entire workflow, from preparatory work to post-processing. In this context, three cuneiform replica tablets will serve as examples on which the Artec scanners will have to prove their worth. Metric analyses based on distance maps, RMSe calculations and density analyses will be carried out to understand metrological differences between these tools. The creation of 3D models of cuneiform tablets is the first step in developing a virtual environment suitable for sharing the archaeological collection with collaborators and other users. The inclusion of semantic information through specific ontologies will be the next step in this important project. Full article

The strap-down inertial navigation system (SINS) and Doppler velocity log (DVL) integrated navigation system are widely used for autonomous underwater vehicles (AUVs). Whereas DVL works in the water tracking mode, the velocity provided by DVL is relative to the current layer and cannot be directly used to suppress the divergence of SINS errors. Therefore, the estimation and compensation of the ocean current velocity play an essential role in improving navigation positioning accuracy. In recent works, ocean currents are considered constant over a short term in small areas. In the common KF algorithm with the ocean current as a state vector, the current velocity cannot be estimated because the current velocity and the SINS velocity error are coupled. In this paper, two virtual metrology filter (VMF) methods are proposed for estimating the velocity of ocean currents based on the properties that the currents remain unchanged at the adjacent moments. New measurement equations are constructed to decouple the current velocity and the SINS velocity error, respectively. Simulations and lake tests show that both proposed methods are effective in estimating the current velocity, and each has its advantages in estimating the ocean current velocity or the misalignment angle. Full article

In order to perform the inspection planning process on the coordinate measuring machine (CMM), it is necessary to model the measuring system with workpiece, CMM and fixture. The metrological analysis of the workpiece is then conducted, followed by the creation of a measurement program for simulation on a virtual measuring machine in a CAD environment. This paper presents the modelling and simulation of a virtual measuring system based on a real CMM using PTC Creo Parametric 5.0 software. The simulation involved programming the measuring path and generating a DMIS (*.ncl) file, which represents the standard modelled types of tolerance. The analysis of the metrology of the measuring part for the given forms of tolerance (location, perpendicularity, flatness, etc.) was performed. The components of the CMM and the assembly with defined kinematic connections are also modelled. Following the simulation and generation of the output DMIS file in PTC Creo using the virtual CMM, the real CMM was programmed and used for actual measurements. Subsequently, a measurement report was generated. The main result of this paper is the modelling of an offline Digital Measuring Twin (DMT) based on the DMIS file. Full article

The material removal rate (MRR) is an important variable but difficult to measure in the chemical–mechanical planarization (CMP) process. Most data-based virtual metrology (VM) methods ignore the large number of unlabeled samples, resulting in a waste of information. In this paper, the semi-supervised deep kernel active learning (SSDKAL) model is proposed. Clustering-based phase partition and phase-matching algorithms are used for the initial feature extraction, and a deep network is used to replace the kernel of Gaussian process regression so as to extract hidden deep features. Semi-supervised regression and active learning sample selection strategies are applied to make full use of information on the unlabeled samples. The experimental results of the CMP process dataset validate the effectiveness of the proposed method. Compared with supervised regression and co-training-based semi-supervised regression algorithms, the proposed model has a lower mean square error with different labeled sample proportions. Compared with other frameworks proposed in the literature, such as physics-based VM models, Gaussian-process-based regression models, and stacking models, the proposed method achieves better prediction results without using all the labeled samples. Full article

Unilateral spatial neglect is a common sensorimotor disorder following the occurrence of a stroke, for which prismatic adaptation is a promising rehabilitation method. However, the use of prisms for rehabilitation often requires the use of specific equipment that may not be available in clinics. To address this limitation, we developed a new software package that allows for the quantification and rehabilitation of unilateral spatial neglect using immersive virtual reality. In this study, we compared the effects of virtual and real prisms in healthy subjects and evaluated the performance of our virtual reality tool (HTC Vive) against a validated motion capture tool. Ten healthy subjects were randomly exposed to virtual and real prisms, and measurements were taken before and after exposure. Our findings indicate that virtual prisms are at least as effective as real prisms in inducing aftereffects (4.39° ± 2.91° with the virtual prisms compared to 4.30° ± 3.49° with the real prisms), but that these effects were not sustained beyond 2 h regardless of exposure modality. The virtual measurements obtained with our software showed excellent metrological qualities (ICC = 0.95, error = 0.52° ± 1.18°), demonstrating its validity and reliability for quantifying deviation during pointing movements. Overall, our results suggest that our virtual reality software (Virtualis, Montpellier, France) could provide an easy and reliable means of quantifying and rehabilitating spatial neglect. Further validation of these results is required in individuals with unilateral spatial neglect. Full article

Purpose: To examine the reliability of scores calculated from virtual reality (VR) games and their association with inhibitory control and cognitive flexibility in young elite rugby players. Methods: Following a familiarization session, seventeen rugby union players completed a session of a modified Stroop test and two sessions of three VR games consisting of (1) memorizing moving targets (Tracker Master); (2) selecting moving targets while avoiding pitfalls (Beat Master—Never Stop); and (3) selecting moving targets with an increasing frequency of appearance (Beat Master—Turbo). Results: The reliability of Beat Master—Never Stop was poor to moderate (0.41 < intraclass coefficient correlation [ICC] < 0.62; 3.2% < standard error of measurement [SEM] < 26.1%), while it was good to very good for Beat Master—Turbo (0.77 < ICC < 0.87; 3.2% < SEM < 18.2%). Regarding Tracker Master, reliability was considered as low to moderate (0.22 < ICC < 0.60; 2.2% < SEM < 6.0%). We found strong associations between Tracker Master and Stroop flexibility scores (−0.55 < r < −0.64), as well as strong to very strong associations between Beat Master—Never Stop scores and the Stroop inhibition score (0.52 < ∣r∣ < 0.84). Conclusions: Considering their metrological properties and their association level with inhibition and flexibility, the sensibility scores of the Beat Master—Never Stop and Tracker Master games should be preferred for monitoring training load, provided at least two familiarization sessions precede them. Full article

The numerical modeling of cardiac electrophysiology has reached a mature and advanced state that allows for quantitative modeling of many clinically relevant processes. As a result, complex computational tasks such as the creation of a variety of electrocardiograms (ECGs) from virtual cohorts of models representing biological variation are within reach. This requires a correct representation of the variability of a population by suitable distributions of a number of input parameters. Hence, the assessment of the dependence and variation of model outputs by sensitivity analysis and uncertainty quantification become crucial. Since the standard metrological approach of using Monte–Carlo simulations is computationally prohibitive, we use a nonintrusive polynomial chaos-based approximation of the forward model used for obtaining the atrial contribution to a realistic electrocardiogram. The surrogate increases the speed of computations for varying parameters by orders of magnitude and thereby greatly enhances the versatility of uncertainty quantification. It further allows for the quantification of parameter influences via Sobol indices for the time series of 12 lead ECGs and provides bounds for the accuracy of the obtained sensitivities derived from an estimation of the surrogate approximation error. Thus, it is capable of supporting and improving the creation of synthetic databases of ECGs from a virtual cohort mapping a representative sample of the human population based on physiologically and anatomically realistic three-dimensional models. Full article

Multiscale approaches for the simulation of materials processing are becoming essential to the industrialization of future nanotechnologies, as they allow for a reduction in production costs and an enhancement of devices and applications. Their integration as modules of “digital twins”, i.e., a combined sequence of predictive chemical–physical simulations and trained black-box techniques, should ideally complement the real sequence of processes throughout all development and production stages, starting from the growth of materials, their functional manipulation and finally their integration in nano-devices. To achieve this framework, computational implementations at different space and time scales are necessary, ranging from the atomistic to the macro-scale. In this paper, we propose a general paradigm for the industrially driven computational modeling of materials by deploying a multiscale methodology based on physical–chemical simulations bridging macro, meso and atomic scale. We demonstrate its general applicability by studying two completely different processing examples, i.e., the growth of group IV crystals through physical vapor deposition and their thermal treatment through pulsed laser annealing. We indicate the suitable formalisms, as well as the advantages and critical issues associated with each scale, and show how numerical methods for the solution of the models could be coupled to achieve a complete and effective virtualization of the process. By connecting the process parameters to atomic scale modifications such as lattice defects or faceting, we highlight how a digital twin module can gain intrinsic predictivity far from the pre-assessed training conditions of black-box “Virtual Metrology” techniques. Full article