Добірка наукової літератури з теми "On-Machine metrology"
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Статті в журналах з теми "On-Machine metrology":
Bibby, Matthew, and Christopher King. "Development of an On-Machine 3D Texture Analyser." Advanced Materials Research 579 (October 2012): 338–47. http://dx.doi.org/10.4028/www.scientific.net/amr.579.338.
Vallejo, Marcela, Carolina de la Espriella, Juliana Gómez-Santamaría, Andrés Felipe Ramírez-Barrera, and Edilson Delgado-Trejos. "Soft metrology based on machine learning: a review." Measurement Science and Technology 31, no. 3 (December 2, 2019): 032001. http://dx.doi.org/10.1088/1361-6501/ab4b39.
Gao, W., H. Haitjema, F. Z. Fang, R. K. Leach, C. F. Cheung, E. Savio, and J. M. Linares. "On-machine and in-process surface metrology for precision manufacturing." CIRP Annals 68, no. 2 (2019): 843–66. http://dx.doi.org/10.1016/j.cirp.2019.05.005.
Li, Duo, Bo Wang, Zheng Qiao, and Xiangqian Jiang. "Ultraprecision machining of microlens arrays with integrated on-machine surface metrology." Optics Express 27, no. 1 (January 3, 2019): 212. http://dx.doi.org/10.1364/oe.27.000212.
Chen, J. S., J. X. Yuan, J. Ni, and S. M. Wu. "Real-time Compensation for Time-variant Volumetric Errors on a Machining Center." Journal of Engineering for Industry 115, no. 4 (November 1, 1993): 472–79. http://dx.doi.org/10.1115/1.2901792.
Blumröder, Ulrike, Ronald Füßl, Thomas Fröhlich, Eberhard Manske, and Rostyslav Mastylo. "FREQUENCY COMB-COUPLED METROLOGY LASERS FOR NANOPOSITIONING AND NANO MEASURING MACHINES." Measuring Equipment and Metrology 82, no. 4 (2021): 36–42. http://dx.doi.org/10.23939/istcmtm2021.04.036.
Lin, Shuo. "Research on the swing and vibration restraint of the 2 MN deadweight machine frame." ACTA IMEKO 9, no. 5 (December 31, 2020): 97. http://dx.doi.org/10.21014/acta_imeko.v9i5.947.
Takahashi, Satoru, Yuki Shimizu, and Yasuhiro Mizutani. "Special Issue on Intelligent Measurement for Advanced Production Engineering." International Journal of Automation Technology 11, no. 5 (August 30, 2017): 681. http://dx.doi.org/10.20965/ijat.2017.p0681.
Ni, J., and S. M. Wu. "An On-Line Measurement Technique for Machine Volumetric Error Compensation." Journal of Engineering for Industry 115, no. 1 (February 1, 1993): 85–92. http://dx.doi.org/10.1115/1.2901643.
Matsubara, Atsushi. "Special Issue on Machine Tool Evaluation." International Journal of Automation Technology 6, no. 2 (March 5, 2012): 109. http://dx.doi.org/10.20965/ijat.2012.p0109.
Дисертації з теми "On-Machine metrology":
Williamson, James. "Dispersed reference interferometry for on-machine metrology." Thesis, University of Huddersfield, 2016. http://eprints.hud.ac.uk/id/eprint/31554/.
Bibby, M. "The development of automatic on-machine metrology." Thesis, University College London (University of London), 2015. http://discovery.ucl.ac.uk/1469718/.
Somthong, Thammarat. "3D freeform surface measurement on coordinate measuring machine using photometric stereo method." Thesis, Brunel University, 2017. http://bura.brunel.ac.uk/handle/2438/15270.
Chouhad, Hassan. "Towards online metrology for proactive quality control in smart manufacturing." Thesis, Paris, HESAM, 2022. http://www.theses.fr/2022HESAE021.
In the traditional manufacturing industry, metrology is an essential element in sanctioning quality at the end of the production line. The innovation brought by concept of smart manufacturing leads to a repositioning of metrology to be proactive at the heart of production by performing the so-called first-time-right manufacturing of parts. The goal of this thesis is therefore to propose a methodological approach for the development of a proactive system, enhanced by AI models, to control the conformity of a product to a specification during machining and to characterize its defects. For this purpose, a first study on the surface aspect was carried out by collecting high-resolution images of coated and cut copper wires that may present defects. The images, taken by a computer vision system based on chromatic confocal imaging, were used to generate different artificial intelligence models. These models can perform segmentation and classification of observed defects. When comparing the accuracy and processing time of the AI models, transfer learning using the mobile-net model showed better performance. To extend the study of surface quality assessment, surface profile measurements on machine tools were performed using non-contact chromatic confocal sensors. Two approaches were performed: i) milling aluminum without tool wear signature, and ii) milling titanium with tool wear signature. In both cutting configurations, machining parameters, surface roughness profiles, and cutting forces were measured to build a dataset for training the prediction models by machine learning. The results showed that the XGboost model presented the best prediction performance and for both scenarios i) and ii). By considering the cutting time in titanium milling, the autoregressive integrated moving average time series prediction model was applied to track the evolution of roughness with tool wear
Verma, Mayank. "An investigation into enabling industrial machine tools as traceable measurement systems." Thesis, University of Bath, 2016. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.707583.
Fiderer, Lukas J. [Verfasser], and Daniel [Akademischer Betreuer] Braun. "New Concepts in Quantum Metrology : Dynamics, Machine Learning, and Bounds on Measurement Precision / Lukas J. Fiderer ; Betreuer: Daniel Braun." Tübingen : Universitätsbibliothek Tübingen, 2020. http://d-nb.info/1212025334/34.
Частини книг з теми "On-Machine metrology":
Nomura, Takashi, and Kazuhide Kamiya. "On-Machine Measurements." In Handbook of Optical Metrology, 867–87. Taylor & Francis Group, 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742: CRC Press, 2015. http://dx.doi.org/10.1201/b18328-38.
Cai, Yindi. "Molecular Dynamics Characterization of a Force Sensor Integrated Fast Tool Servo for On-Machine Surface Metrology." In Precision Manufacturing, 1–28. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-10-4912-5_21-1.
Cai, Yindi. "Molecular Dynamics Characterization of a Force Sensor Integrated Fast Tool Servo for On-Machine Surface Metrology." In Precision Manufacturing, 601–29. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-10-4938-5_21.
Kamiya, Kazuhide, and Takashi Nomura. "On-Machine Measurements." In Handbook of Optical Metrology. CRC Press, 2009. http://dx.doi.org/10.1201/9781420019513.ch30.
Nomura, Takashi, and Kazuhide Kamiya. "On-Machine Measurements." In Handbook of Optical Metrology, 867–87. CRC Press, 2017. http://dx.doi.org/10.1201/b18328-34.
Gao, Wei. "On-machine roll profiler." In Surface Metrology for Micro- and Nanofabrication, 337–70. Elsevier, 2021. http://dx.doi.org/10.1016/b978-0-12-817850-8.00010-8.
Jiang, Xianqian J., Feng Gao, Haydn Martin, James Williamson, and Duo Li. "On-Machine Metrology for Hybrid Machining." In Hybrid Machining, 239–68. Elsevier, 2018. http://dx.doi.org/10.1016/b978-0-12-813059-9.00010-5.
Gao, Wei. "On-machine atomic force microscope." In Surface Metrology for Micro- and Nanofabrication, 305–36. Elsevier, 2021. http://dx.doi.org/10.1016/b978-0-12-817850-8.00009-1.
Gao, Wei. "On-machine length gauge surface profiler." In Surface Metrology for Micro- and Nanofabrication, 225–69. Elsevier, 2021. http://dx.doi.org/10.1016/b978-0-12-817850-8.00007-8.
Gao, Wei. "On-machine air-bearing surface profiler." In Surface Metrology for Micro- and Nanofabrication, 271–304. Elsevier, 2021. http://dx.doi.org/10.1016/b978-0-12-817850-8.00008-x.
Тези доповідей конференцій з теми "On-Machine metrology":
Morris, Michael North. "Dynamic Interferometry for On-Machine Metrology." In Frontiers in Optics. Washington, D.C.: OSA, 2010. http://dx.doi.org/10.1364/fio.2010.stua3.
Cheng, Hsiang Nan, Katherine Overend, Yu Zhang, and Rongguang Liang. "On-machine metrology system (Conference Presentation)." In Dimensional Optical Metrology and Inspection for Practical Applications VI, edited by Song Zhang and Kevin G. Harding. SPIE, 2017. http://dx.doi.org/10.1117/12.2264882.
Novini, Amir R. "Fundamentals of on-line gauging for machine vision." In Industrial Vision Metrology, edited by Sabry F. El-Hakim. SPIE, 1991. http://dx.doi.org/10.1117/12.48232.
Dong, Lizhi, Wenjin Liu, Ping Yang, Shuai Wang, Xing He, and Bing Xu. "Automatic online laser resonator alignment based on machine vision: analysis." In SPIE Optical Metrology, edited by Jürgen Beyerer and Fernando Puente León. SPIE, 2015. http://dx.doi.org/10.1117/12.2184585.
Lai, Tao, Junfeng Liu, Shanyong Chen, Chaoliang Guan, Guipeng Tie, and Quan Liao. "Out-of-squareness measurement on ultra-precision machine based on the error separation." In SPIE Optical Metrology, edited by Bernd Bodermann, Karsten Frenner, and Richard M. Silver. SPIE, 2017. http://dx.doi.org/10.1117/12.2270171.
Jiang, Lixing, Kuoyuan Sun, Fulai Zhao, and Xiangyang Hao. "Automatic detection system of shaft part surface defect based on machine vision." In SPIE Optical Metrology, edited by Jürgen Beyerer and Fernando Puente León. SPIE, 2015. http://dx.doi.org/10.1117/12.2184728.
Jiang, Jiabin, Xiang Xiao, Guohua Feng, Zichen Lu, and Yongying Yang. "Detection and classification of glass defects based on machine vision." In Applied Optical Metrology III, edited by Erik Novak and James D. Trolinger. SPIE, 2019. http://dx.doi.org/10.1117/12.2528654.
Bruzzone, Elisabetta, and Fulvia Mangili. "Calibration of a CCD camera on a hybrid coordinate measuring machine for industrial metrology." In Industrial Vision Metrology, edited by Sabry F. El-Hakim. SPIE, 1991. http://dx.doi.org/10.1117/12.48240.
Ermolaev, Petr A., and Maxim A. Volynsky. "Interferometric signals analysis based on the extended Kalman filter tuned by machine learning technique." In SPIE Optical Metrology, edited by Peter Lehmann, Wolfgang Osten, and Armando Albertazzi Gonçalves. SPIE, 2017. http://dx.doi.org/10.1117/12.2269653.
El-Hakim, Sabry F. "A Stereo Vision System For On-Machine Dimensional Metrology." In SPIE 1989 Technical Symposium on Aerospace Sensing, edited by Mohan M. Trivedi. SPIE, 1989. http://dx.doi.org/10.1117/12.969281.