Relevant bibliographies by topics / Geometric accuracy of the machine

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Geometric accuracy of the machine'

Author: Grafiati
Published: 28 June 2021
Last updated: 29 July 2025

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Journal articles on the topic "Geometric accuracy of the machine"

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Holub, Michal, and Jiri Rosenfeld. "Geometric Accuracy of Large Machine Tools." Acta Mechanica Slovaca 24, no. 3 (2020): 56–62. http://dx.doi.org/10.21496/ams.2020.036.

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Berus, Lucijano, Jernej Hernavs, David Potocnik, Kristijan Sket, and Mirko Ficko. "Enhancing Manufacturing Precision: Leveraging Motor Currents Data of Computer Numerical Control Machines for Geometrical Accuracy Prediction Through Machine Learning." Sensors 25, no. 1 (2024): 169. https://doi.org/10.3390/s25010169.

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Direct verification of the geometric accuracy of machined parts cannot be performed simultaneously with active machining operations, as it usually requires subsequent inspection with measuring devices such as coordinate measuring machines (CMMs) or optical 3D scanners. This sequential approach increases production time and costs. In this study, we propose a novel indirect measurement method that utilizes motor current data from the controller of a Computer Numerical Control (CNC) machine in combination with machine learning algorithms to predict the geometric accuracy of machined parts in real
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Wang, Lina, Xingxing Liu, Wenjie Tian, and Dawei Zhang. "Geometric Accuracy Design and Tolerance Allocation of Precision Horizontal Machining Centers." Machines 13, no. 3 (2025): 187. https://doi.org/10.3390/machines13030187.

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As the structural complexity of machined components increases and the pace of product updates accelerates, the demands for machining precision in CNC machine tools are becoming increasingly rigorous. Consequently, the continuous enhancement of machining accuracy in machine tools presents a significant challenge that must be addressed within the realms of machine tool innovation and the development of manufacturing equipment. This paper conducts a comprehensive investigation into the tolerance optimization allocation method for geometric accuracy in precision horizontal machining centers utiliz
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Li, Saichen, Huimin Kang, Zelong Li, et al. "Development of a Large-Aperture Coordinate Precision Measurement Instrument Using Differential Geometric Error Weighting." Applied Sciences 14, no. 22 (2024): 10125. http://dx.doi.org/10.3390/app142210125.

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The accuracy of traditional measuring machines is affected by the measuring range and sensitive geometric errors, and it is not possible to combine large caliber and high-precision measurements. This study proposes a differential geometric error-weighting method for designing a high-precision, large-diameter measuring machine. The machine utilized a zero-Abbe arm structure and applied the rigid body theory and small-angle hypothesis to model geometric errors. Weights were calculated for 23 geometric errors, identifying eight sensitive ones. A picometer-precision laser interferometer (quDIS) wi
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IBARAKI, Soichi. "How Accurate is the Motion? : Geometric Accuracy Measurement for Machine Tools." Journal of the Society of Mechanical Engineers 118, no. 1164 (2015): 672–75. http://dx.doi.org/10.1299/jsmemag.118.1164_672.

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Morimoto, Yoshitaka, Keisuke Nakato, and Motoshi Gontani. "Accuracy Evaluation of 5-Axis Machining Center Based on Measurements of Machined Workpiece – Evaluation of Accuracy of 5-Axis Controlled Machining Center –." International Journal of Automation Technology 6, no. 5 (2012): 675–81. http://dx.doi.org/10.20965/ijat.2012.p0675.

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A new method for evaluating the geometrical accuracy of a 5-axis Machining Center (MC) based on the measurement results of the machined workpiece has been developed. The strategy behind our method is to utilize, because of its accuracy, a Coordinates Measuring Machine (CMM) as a master gauge. Thus, the machine operator machines the workpiece and a technologist of precise measurement takes the measurements. In our study, non-rotational machining is utilized to copy and trace the machine trajectory on the workpiece, minimizing the machining error. The profiles of the machined workpiece are measu
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Cheng, Qiang, Hongwei Zhao, Zhifeng Liu, Cui Zhang, and Peihua Gu. "Robust geometric accuracy allocation of machine tools to minimize manufacturing costs and quality loss." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 230, no. 15 (2016): 2728–44. http://dx.doi.org/10.1177/0954406215600398.

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With increasing demands of machining accuracy, designing of machine tools for satisfactory performance using cost-effective geometric accuracy configurations is becoming a complex problem to the machine tool manufacturers. In this paper, a novel robust accuracy allocation method is proposed for multi-axis machine tools based on multi-objective quality and cost trade-offs. To model the volumetric accuracy of machine tool based on geometric errors, the multi-body system theory was introduced. A manufacturing cost model for the machine tool components with a significant effect on geometric errors
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Hoang, Trung Kien, and Nguyen Minh Duc Ta. "Machining Based Geometric Error Estimation Method for 3-Axis CNC Machine." Applied Mechanics and Materials 889 (March 2019): 469–74. http://dx.doi.org/10.4028/www.scientific.net/amm.889.469.

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Computer numerical control (CNC) machine tool plays an extremely significant role in any manufacturing industry due to its automation and high accuracy. Keeping the CNC machine tool at its highest performance to meet the demand of high accuracy machining is always significant. To maintain the accuracy of a machine tool over the time, it is important to measure and compensate the geometric error, one of the main error source of machine tool, especially when the machine get old. There are totally 21 geometrical errors in a 3-axis machine tool including three translational errors and three rotati
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Yang, Lin, Jin Yuan Wang, Rui Nan Wu, and Wei Wu. "Machine Slideway Wear to the Precision of the Whole Machine Impact." Applied Mechanics and Materials 229-231 (November 2012): 2474–77. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.2474.

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This paper studies the influence of machine slideway precision on the overall accuracy of machine tools, and puts forward the root causes of the decline in accuracy of machine tool guide is rail wear, the decline of rail accuracy will impact on the adjacent unit cell, thus decline the accuracy of the machined parts; Finally takes floor-type milling & boring machine as research object, bases on geometric error models of the theory of multi-body system to describe the spindle box rail wear trends and establish relationship between the spindle box rail wear and the machine precision.
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Li, Dianxin, Pingfa Feng, Jianfu Zhang, Dingwen Yu, and Zhijun Wu. "An identification method for key geometric errors of machine tool based on matrix differential and experimental test." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 228, no. 17 (2014): 3141–55. http://dx.doi.org/10.1177/0954406214527272.

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This paper presents a key geometric errors identification method for machine tools based on matrix differential and experimental test. An error model for a machine tool was established by regarding the three-axis machining center as a multi-body system. The sensitivity coefficients of the machining error with respect to the geometric errors were determined using the matrix differential method, and the degree of influence of the geometric errors on the machining accuracy under ideal conditions was discussed. Using the 12-line method, 21 geometric errors of the machine tool were identified, allo
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Dissertations / Theses on the topic "Geometric accuracy of the machine"

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Cross, P. M. "An analysis of the geometric instability of steady supported grinding." Thesis, University of Bristol, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.384445.

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Fletcher, Simon. "Computer aided system for intelligent implementation of machine tool error reduction methodologies." Thesis, University of Huddersfield, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368312.

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Suchomel, Kamil. "Vlivy výrobních technologií na geometrickou a rozměrovou přesnost obrobků." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2017. http://www.nusl.cz/ntk/nusl-319263.

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The aim of the diploma thesis is to describe influences of selected production technologies on geometrical and dimensional accuracy of workpieces. Specific technologies - turning, milling and grinding and the machines on which these technologies will be implemented - a vertical lathe, a portal milling machine and a center grinder are described in this thesis. Additionally a procedure is created for adding geometric errors to a tri-axial machine tool to describe the entire working area of the machine in terms of errors. Subsequently an analysis of each geometric error is created for each machin
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Vala, Michal. "Testování technologie on-the-fly přístrojem LaserTRACER." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2017. http://www.nusl.cz/ntk/nusl-319262.

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This diploma thesis describes realization and testing on-the-fly measurement using tracking interferometer. This measurement enables to achieve higher amount of measured points and decrease time of machine tool calibration. Calibration and verification values of machine parameters, as well as time of measurement and other details of this method are compared with results of conventional method called trigger. To evaluate the quality of volumetric compensation created from calibration values, we use verification measurement of circular interpolation.
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Velič, Samuel. "Měření obrobků na obráběcích strojích pomocí obrobkové sondy." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-417728.

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This diploma thesis deals with the influence of electronic compensation on accuracy of the measurement using the touch probe. The theoretical part concerns touch probes, specifically their classification, principles of working and applications. This part also includes devices used later in the experiment, particularly double ballbar, laser interferometer and LaserTRACER. The Practical part describes an experiment, demonstrating the correlation between the accuracy improvement of the touch probe and the electronic compensation’s level. All measurements were executed in accordance with the norm
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Pokorný, Zdeněk. "Zpracování dat z měření na obráběcích strojích." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2018. http://www.nusl.cz/ntk/nusl-382195.

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The Master’s thesis deals with the precision of machine tools, especially with the three-axis vertical milling machine. It is structurally divided into a theoretical and practical part. While the theoretical part focuses on problems of geometric errors and measuring devices, the practical one is devoted to the machine tool being tested. In this case, the data processing and the proposed statistical analysis are essential, and at the end of the thesis another possible way of developing the data processing is outlined.
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Únar, Jan. "Posouzení geometrické přesnosti obráběcího centra pomocí digitálních inklinometrů." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2021. http://www.nusl.cz/ntk/nusl-444307.

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This diploma thesis deals with assessment of geometric accuracy of machining center MCV 754 QUICK. BlueSYSTEM digital inclinometers from WYLER AG, XL-80 laser interferometer from RENISHAW, Ballbar QC20-W from RENISHAW and LaserTRACER self-guiding laser interferometer from ETALON AG were used to measure accuracy. Error of the X straightness in the direction of the Z axis was assessed. The first part of the paper describes the geometric accuracy of the machine, currently available instruments for measuring geometric accuracy and an explanation of straightness. The second part consists of the des
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Mišún, Filip. "Návrh automatického cyklu pro posuzování způsobilosti měření obrobkovou sondou na obráběcím centru." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2021. http://www.nusl.cz/ntk/nusl-443252.

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This diploma thesis describes the procedures of individual electronic compensations for CNC machines used to increase the accuracy of machines. This part is followed by the determining tolerance of the measuring and the influence of individual electronic compensations based on measured data using touch probe and calibrated standards according to VDA 5 norm.
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Lintott, Andrew B. "Geometric modelling and accuracy enhancement of parallel manipulators." Thesis, University of Canterbury. Mechanical Engineering, 2000. http://hdl.handle.net/10092/6159.

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The geometric analysis and accuracy enhancement of parallel topology robots is of theoretical interest as well as having potential for application in industrial settings where parallel robots are used for tasks in which positional accuracy is important. This work presents new techniques for modelling of closed loop mechanisms and applies these experimentally in the calibration of a real parallel topology robot: The Delta robot. This work extends the current literature on serial robot calibration into the realm of parallel robots and presents a systematic approach which does not require the mod
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Dimitriadis, Alexis. "Assessing the dosimetric and geometric accuracy of stereotactic radiosurgery." Thesis, University of Surrey, 2017. http://epubs.surrey.ac.uk/813888/.

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Stereotactic radiosurgery (SRS) is a non-invasive treatment predominantly used for the management of malignant and benign brain tumours. The treatment can be delivered by various platforms in a single fraction where a high dose of radiation is delivered to the target whilst the surrounding healthy tissue is spared. This requires a high degree of accuracy in terms of the dose level delivered but also in terms of geometric precision. The purpose of this work was to identify the variations of SRS practice in the UK and develop a novel method compatible with all practices, capable of assessing the
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Books on the topic "Geometric accuracy of the machine"

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T, Portman V., and Dunaevsky V. V, eds. Accuracy of machine tools. ASME Press, 1988.

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Kanatani, Kenʼichi. Geometric computation for machine vision. Clarendon Press, 1993.

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Etesami, Faryar. Geometric Tolerancing Standard to Machine Design. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-47585-6.

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Institution, British Standards. Accuracy of machine tools and methods of test. BSI, 1988.

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Institution, British Standards. Accuracy of machine tools and methods of test. BSI, 1988.

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Postlethwaite, Scott R. Electronic based accuracy enhancement of CNC machine tools. The Polytechnic, 1992.

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Institution, British Standards. Accuracy of machine tools and methods of test. BSI, 1988.

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Jywe, W. A computer-aided accuracy testing device for machine tools. UMIST, 1992.

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Marciniak, Krzysztof. Geometric modelling for numerically controlled machining. Oxford University Press, 1991.

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Robinson, Mark John. Limits to the accuracy of dimensional measurement using machine vision. University of Manchester, 1994.

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Book chapters on the topic "Geometric accuracy of the machine"

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Holub, Michal. "Geometric Accuracy of Machine Tools." In Materials Forming, Machining and Tribology. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03822-9_3.

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Wang, Sitong, Gaiyun He, Dawei Zhang, Faze Chen, and Rui Wang. "Geometric Accuracy Innovative Design Method for Machine Tool." In Advances in Mechanism and Machine Science. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-45709-8_65.

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Feng, Y., Q. Wang, D. Wu, and W. Gao. "Machine Learning-Aided Nonlinear Dynamic Analysis of Engineering Structures." In Lecture Notes in Civil Engineering. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3330-3_36.

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AbstractA machine learning (ML) technique was used to assist in the dynamic analysis of mixed geometric and material nonlinearities of real-life engineering structures. Various types of inputs of system properties were considered in the 3D dynamic geometric elastoplastic analysis, giving a series of realistic nonlinear descriptions of complex, large deformation structural behaviors. To resolve the numerical challenges of solving the mixed nonlinear problems, a newly established ML technique using a new cluster-based extended support vector regression (X-SVR) algorithm was applied. With this te
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Regus, Michal, Bartosz Gapinski, Piotr Czajka, and Piotr Jablonski. "Studies of Geometric Accuracy of Polygons Machined by Polygonal Turning Technique." In Lecture Notes in Mechanical Engineering. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68619-6_75.

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Bertrand, Ambre, Carolyna Yamamoto, Giulia Monopoli, et al. "Augmentation of Cardiac Ischemic Geometry for Improving Machine Learning Performance in Arrhythmic Risk Stratification." In Computational Physiology. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-53145-3_3.

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AbstractVentricular arrhythmias frequently occur as a complication of myocardial infarction (MI), due to significant changes in the heart’s structure and electrophysiology. If left untreated, these alterations may lead to sudden cardiac death (SCD). It is therefore critical to evaluate risk prediction accurately in post-infarction patients to enable early intervention and improve patient outcomes. This work introduces a novel approach to improve arrhythmia risk assessment in post-infarction patients. We propose a new pipeline to build physiologically realistic image-based models of patient hea
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Xin, Cun, Dangfeng Yang, Xiaodong Liu, Yong Huang, and Xueming Qian. "Research on Dam Crack Identification Method Based on Multi-source Information Fusion." In Lecture Notes in Civil Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-9184-2_1.

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AbstractCracks as the main safety concern of dams, high-precision identification of dam cracks is of great application value and scientific significance to ensure the safety of dams. The paper proposes a dam crack identification method based on multi-source information fusion. Specifically, image gray scale and geometric features are extracted based on the image information. And then a single crack identification model based on Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), XGBoost, and BP Neural Network are established based on the features, respectively. Finally, a mul
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Yao, Wei, and Jianwei Wu. "Airborne LiDAR for Detection and Characterization of Urban Objects and Traffic Dynamics." In Urban Informatics. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8983-6_22.

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AbstractIn this chapter, we present an advanced machine learning strategy to detect objects and characterize traffic dynamics in complex urban areas by airborne LiDAR. Both static and dynamical properties of large-scale urban areas can be characterized in a highly automatic way. First, LiDAR point clouds are colorized by co-registration with images if available. After that, all data points are grid-fitted into the raster format in order to facilitate acquiring spatial context information per-pixel or per-point. Then, various spatial-statistical and spectral features can be extracted using a cu
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Ben-Hanan, U., U. Eckert, M. Mende, A. Weiss, R. Wertheim, and U. Azaria. "Development of a Pneumatic Clamping System with Position and Force Control Machining." In Lecture Notes in Mechanical Engineering. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-28839-5_21.

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AbstractPrecision machining plays a vital role in modern, efficient, and sustainable manufacturing. Monitoring and controlling the clamping forces can influence positioning accuracy, workpiece deformation, thus improving the production outcome. The clamping force must be adapted to the cutting forces, workpiece geometry, and material properties to improve accuracy and control workpiece deformation during machining. The best devices available have a repeatability of ±1 µm, however, with limited precision and repeatability when re-clamping the workpiece. This paper presents the newly developed h
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Poorahad Anzabi, Pooria, Mahmoud R. Shiravand, and Shima Mahboubi. "Machine Learning-Aided Prediction of Seismic Response of RC Bridge Piers Exposed to Chloride-Induced Corrosion." In Lecture Notes in Civil Engineering. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-69626-8_118.

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AbstractDifferent environmental issues such as carbonation and corrosion due to chloride threaten aging reinforced concrete (RC) bridges that are in service in areas highly prone to corrosion and earthquakes. Significant experimental and numerical efforts have been put into scrutinizing the effect of corrosion on nonlinear behavior of structural elements. With the rapid development of artificial intelligence, useful methods are now provided to allow for the assessment of such bridges without the drawbacks and limitations of the experimental and numerical methods. In this paper, four machine le
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Pham Van, Hung, Canh Nguyen Van, and Duong Nguyen Thuy. "A Method of Determination of the Remaining Geometrical Accuracy of Lathe Machine Based on the Wear of Slideway." In The AUN/SEED-Net Joint Regional Conference in Transportation, Energy, and Mechanical Manufacturing Engineering. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1968-8_71.

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Conference papers on the topic "Geometric accuracy of the machine"

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Ledenyák, Daniel, Tamás Rosta, and Mátyás Andó. "Improve the Practical Usability of Ballbar Machine Tool Verification." In 10th International Scientific Conference on Advances in Mechanical Engineering. Trans Tech Publications Ltd, 2025. https://doi.org/10.4028/p-hws2i5.

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The ballbar measurement process is a useful friendly and quick way to verify a machine tool’s accuracy. The ballbar is a telescopic linear sensor with two precision balls at both ends. During the measurement, the sensor’s end is precisely located with the support of the magnetic cups, resulting in the +/- micrometer accurate measurement of radius in each of points of circular path. A CNC machine’s accuracy could be affected with several defects like defective tooling, worn spindles, or issues with workpiece clamping. The errors related to the machine are known as geometric, play related or dyn
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Cornelius, Jason, Zachary Miles, Anthony Comer, et al. "Long-Range Mars Rotorcraft Design Optimization using Machine Learning." In Vertical Flight Society 81st Annual Forum and Technology Display. The Vertical Flight Society, 2025. https://doi.org/10.4050/f-0081-2025-364.

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Simulation data consisting of multiple fidelity levels were generated using Graphical Processing Unit (GPU) resources on the NASA supercomputers. First, two large aerodynamic simulation databases were generated for geometric perturbations over a range of flight conditions for a hex-rotor bi-plane tailsitter aircraft. Results were visualized using the NASA Advanced Supercomputing Division's Hyperwall to improve the geometric design constraints. More than 3,000 full aircraft aerodynamic simulations were run using GPU enabled OVERFLOW with an actuator disk model to generate the airframe aerodynam
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Holub, Michal, and Josef Knobloch. "Geometric accuracy of CNC machine tools." In 2014 16th International Conference on Mechatronics - Mechatronika (ME). IEEE, 2014. http://dx.doi.org/10.1109/mechatronika.2014.7018268.

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Jones, Michael, Poojith Chowdary Chigurupati, and Hossein Taheri. "Development of a Geometric Accuracy Machine Vision Application for Metal Castings." In ASME 2024 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2024. https://doi.org/10.1115/imece2024-143240.

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Abstract Metal castings provide critical products to several industries such as aerospace, medical, and automobile. A prominent level of geometric accuracy is required in high-value casting components to ensure an adequate level of quality. While traditional methods of measuring critical features on metal castings such as laser scanning measurements have proven effective to determine geometric accuracy, these techniques are often time consuming and require costly equipment and labor time. The aspect of geometry measurement in Industry 4.0 involves the application of advanced digital technologi
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Etesami, Faryar, and Tim Griffin. "Characterizing the Accuracy of FDM Rapid Prototyping Machines for Machine Design Applications." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-64972.

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This paper presents experiment-based formulas that predict the geometric accuracy of Fused Deposition Modeling (FDM) rapid prototyping (RP) machines in a form suitable for fit and function applications. The proposed method establishes the accuracy of several base-level geometry characteristics such as line straightness and circularity through direct measurements. Statistical analyses are used to establish reliable prediction formulas for the base-level geometry characteristics. The base-level accuracy measures are then used to develop models for higher-level geometric accuracies such as orient
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Liu, Xinyu. "Experimental Investigation of Micro-Milling Accuracy Using On-Machine Measurement System." In ASME 2010 International Manufacturing Science and Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/msec2010-34245.

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In this paper, we proposed an error decomposition method, in which some major error components can be experimentally estimated using an on-machine measurement (OMM) system. Unlike the conventional machining, the geometric error of a micro-tool, i.e., the deviation of the effective tool diameter from a nominal value, becomes a dominant factor affecting the machining accuracy. The error stems from both the tool fabrication error and the dynamic runout of the spindle system under high rpm. An on-machine measurement system based on a non-contact confocal laser sensor was developed that can accurat
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Qi, Baobao, Qiang Cheng, Zhifeng Liu, and Dongyang Sun. "To Identify Key Geometric Errors of 3-Axis NC Machine Tool by Machining Accuracy Failure Mode Analysis." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-97016.

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Abstract Machine tools usually cut two or more surfaces after the work piece clamped on work table. In order to improve the machining accuracy and optimize accuracy design, it is hoped that the geometric errors that influence the accuracy of machined surface prominently can be known beforehand, so the adjustment will be carried out with a definite objective rather than without any clue. Because the machining accuracy of each direction in 3-D space is different value, in this paper, machining accuracy failure mode was defined as the various combination of the machining accuracy of each directio
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Kim, Gee-Hong, Seung-Woo Kim, and SangGun Lim. "Automatic inspection of geometric accuracy of optical fiber ferrules by machine vision." In Optics and Optoelectronic Inspection and Control: Techniques, Applications, and Instruments, edited by Shulian Zhang and Wei Gao. SPIE, 2000. http://dx.doi.org/10.1117/12.403848.

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Shaowei Zhu, Guofu Ding, Lei Jiang, Yu Peng, Shuwen Ma, and Kaiyin Yan. "Machining accuracy improvement of five-axis machine tools by geometric error compensation." In International Conference on Advanced Technology of Design and Manufacture (ATDM 2010). IET, 2010. http://dx.doi.org/10.1049/cp.2010.1321.

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Decker, Nathan, and Qiang Huang. "Geometric Accuracy Prediction for Additive Manufacturing Through Machine Learning of Triangular Mesh Data." In ASME 2019 14th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/msec2019-3050.

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Abstract While additive manufacturing has seen tremendous growth in recent years, a number of challenges remain, including the presence of substantial geometric differences between a three dimensional (3D) printed part, and the shape that was intended. There are a number of approaches for addressing this issue, including statistical models that seek to account for errors caused by the geometry of the object being printed. Currently, these models are largely unable to account for errors generated in freeform 3D shapes. This paper proposes a new approach using machine learning with a set of pred
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Reports on the topic "Geometric accuracy of the machine"

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Cheng, DingXin. Development of the Roadway Pothole Management Program. Mineta Transportation Institute, 2024. http://dx.doi.org/10.31979/mti.2024.2306.

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Addressing the issue of potholes is a primary concern for maintaining urban infrastructure. The research team has developed a prototype pothole management program. The program includes a mobile application and two machine learning models. The mobile app enables users to upload images of potholes, report relevant information, and provide driving directions to the pothole location. With the help of this application, the user can seamlessly capture images of the potholes, record pertinent information, and submit the data for necessary action. The mobile application is an essential tool in the Pot
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Smith, Michael, Esha Datta, Richard Field, et al. Geometric Measures of Trustworthiness for Machine Learning Predictions. Office of Scientific and Technical Information (OSTI), 2024. https://doi.org/10.2172/2480174.

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Kirka, Michael, Yousub Lee, Daniel Ryan, and David Adair. Assessment of High Gamma Prime Ni-base Superalloy Processability, Geometric Accuracy, and Component Fabricability. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1659625.

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Klingmann, J. Accuracy enhancement of high-productivity machine tools CRADA No. TC-0161-91. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/757021.

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Slone, Scott Michael, Marissa Torres, Nathan Lamie, Samantha Cook, and Lee Perren. Automated change detection in ground-penetrating radar using machine learning in R. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49442.

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Ground-penetrating radar (GPR) is a useful technique for subsurface change detection but is limited by the need for a subject matter expert to process and interpret coincident profiles. Use of a machine learning model can automate this process to reduce the need for subject matter expert processing and interpretation. Several machine learning models were investigated for the purpose of comparing coincident GPR profiles. Based on our literature review, a Siamese Twin model using a twinned convolutional network was identified as the optimum choice. Two neural networks were tested for the interna
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Klingman, J., and R. Kegg. Accuracy Enhancement of High-Productivity Machine Tools Final Report CRADA No. TC-0161-91. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1430940.

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Cui, Yonggang, O. Dim, C. Soto, et al. Using machine learning to improve efficiency and accuracy of burnup measurements at PBR reactors. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1830207.

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Garcia-Chavez, Leslie. Machine Learning for Seismic Signals: Evaluating the Accuracy of Phase Picking for Oklahoma Earthquakes. Office of Scientific and Technical Information (OSTI), 2024. http://dx.doi.org/10.2172/2281498.

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9

Vickers, David, and Heath Spidle. PR-015-203900-R01 Reliability Detection and Accuracy of CPM Detection Systems Using Machine Learning. Pipeline Research Council International, Inc. (PRCI), 2022. http://dx.doi.org/10.55274/r0012211.

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This report documents the result of research conducted by Southwest Research Institute (SwRI�) for the Pipeline Research Council International (PRCI) into the development of a Machine Learning (ML) model for improving the detection of leaks in liquid-carrying pipelines. Operators were surveyed as to their use of CPM systems for leak detection. Several operators provided data to support the research. The data was collected, curated, and analyzed by SwRI. Several ML models were investigated. A framework was developed to allow operators to use their own data to generate ML models for their pipeli
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Alwan, Iktimal, Dennis D. Spencer, and Rafeed Alkawadri. Comparison of Machine Learning Algorithms in Sensorimotor Functional Mapping. Progress in Neurobiology, 2023. http://dx.doi.org/10.60124/j.pneuro.2023.30.03.

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Objective: To compare the performance of popular machine learning algorithms (ML) in mapping the sensorimotor cortex (SM) and identifying the anterior lip of the central sulcus (CS). Methods: We evaluated support vector machines (SVMs), random forest (RF), decision trees (DT), single layer perceptron (SLP), and multilayer perceptron (MLP) against standard logistic regression (LR) to identify the SM cortex employing validated features from six-minute of NREM sleep icEEG data and applying standard common hyperparameters and 10-fold cross-validation. Each algorithm was tested using vetted feature
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