Abstract
Industry 4.0, on which many different studies have already been written, brings with it a completely different outlook, especially in IT. Cyber-physical systems, the Internet of Things, networks and cloud-based big data, artificial intelligence, and robotics are essential elements that have also found their way into Metrology 4.0, sometimes called Metrology of the Future. In the paper, measurement technologies for Metrology 4.0 were presented. They belong to coordinate measurement techniques in different scales: macro, micro, and meso. Optical scanning and computed tomography were discussed, focusing on achievable big data. From an IT point of view, the use of artificial intelligence was shown. The possibility of using augmented and virtual reality was also depicted with a short note on cybersecurity. Finally, some ideas regarding Metrology for the Future were briefly presented. It will probably be more oriented to man and use the planet’s natural resources more efficiently. Systems will be based on objects working together, with the definition of connections using the idea of blockchain. And as the data overgrows, data management systems and applications will appear, allowing the user to select the most relevant data.
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References
Sladek, J.: Coordinate Metrology Accuracy of Systems and Measurements. Springer Tracts in Mechanical Engineering, Berlin (2016)
Hocken, R.J., Pereira, P.H.: Coordinate Measuring Machines and Systems. CRC Press, Boca Raton (2012)
Pavlenko, I., Ivanov, V., Gusak, O., Liaposhchenko, O., Sklabinskyi, V.: Parameter identification of technological equipment for ensuring the reliability of the vibration separation process. In: Knapcikova, L., Balog, M., Perakovic, D., Perisa, M. (eds.) 4th EAI International Conference on Management of Manufacturing Systems. EICC, pp. 261–272. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-34272-2_24
Isa, M.A., Lazoglu, I.: Design and analysis of a 3D laser scanner. Measurement 111, 122–133 (2017). https://doi.org/10.1016/j.measurement.2017.07.028
Rekas, A., et al.: Analysis of tool geometry for the stamping process of large-size car body components using a 3D optical measurement system. Materials 14, 7608 (2021). https://doi.org/10.3390/ma14247608
Swojak, N., Wieczorowski, M., Jakubowicz, M.: Assessment of selected metrological properties of laser triangulation sensors. Measurement 176, 109190 (2021). https://doi.org/10.1016/j.measurement
Carmignato, S., Dewulf, W., Leach, R. (eds.): Springer, Cham (2018). https://doi.org/10.1007/978-3-319-59573-3
Gapinski, B., Wieczorowski, M., Mietliński, P., Mathia, T.G.: Verification of computed tomograph for dimensional measurements. In: Diering, M., Wieczorowski, M., Harugade, M., Pereira, A. (eds.) Advances in Manufacturing III. Manufacturing 2022. Lecture Notes in Mechanical Engineering, pp. 142−155. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-03925-6_13
Sadaoui, S.E., Mehdi-Souzani, C., Lartigue, C.: Multisensor data processing in dimensional metrology for collaborative measurement of a laser plane sensor combined to a touch probe. Measurement 188, 110395 (2022). https://doi.org/10.1016/j.measurement.2021.110395
Zaloga, V., Yashyna, T., Dynnyk, O.: Analysis of the theories for assessment of the quality management product efficiency. J. Eng. Sci. 5(2), B1–B6 (2018). https://doi.org/10.21272/jes.2018.5(2).b1
Sayles, R.A., Thomas, T.R.: Mapping a small area of a surface. J. Phys. E 9(10), 855–861 (1976)
Herraez, J., Martinez, J.C., Coll, E., Martin, M.T., Rodriguez, J.: 3D modeling by means of videogrammetry and laser scanners for reverse engineering. Measurement 87, 216–227 (2016). https://doi.org/10.1016/j.measurement.2016.03.005
Brown, C.A., Charles, P.D.: Fractal analysis of topographic data by the patchwork method. Wear 161, 61–67 (1993)
Kaščak, J., Husár, J., Knapčíková, L., Trojanowska, J., Ivanov, V.: Conceptual use of augmented reality in the maintenance of manufacturing facilities. In: Trojanowska, J., Kujawińska, A., Machado, J., Pavlenko, I. (eds.) MANUFACTURING 2022. LNME, pp. 241–252. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-99310-8_19
Wieczorowski, M., Kucharski, D., Sniatala, P., Krolczyk, G., Pawlus, P., Gapinski, B.: Theoretical considerations on application of artificial intelligence in coordinate metrology. In: 6th International Conference on Nanotechnology for Instrumentation and Measurement, NanofIM 2021 (2021). https://doi.org/10.1109/NanofIM54124.2021.9737344
Schwartz, B.: The Paradox of Choice. Harper Collins Publishers (2016)
Khanafer, M., Shirmohammadi, S.: Applied AI in instrumentation and measurement: the deep learning revolution. IEEE Instrum. Meas. Mag. 23(6), 10–17 (2020). https://doi.org/10.1109/MIM.2020.9200875
Seewig, J.: Linear and robust Gaussian regression filters. J. Phys. Conf. Ser. 13(1), 254–257 (2005)
Pawlus, P., Reizer, R., Letocha, A., Wieczorowski, M.: Morphological filtration of two-process profiles. Bull. Pol. Acad. Sci. Tech. Sci. 67(1), 107–113 (2019). https://doi.org/10.24425/bpas.2019.127339
Zeng, W., Jiang, X., Scott, P.J.: A generalised linear and nonlinear spline filter. Wear 271, 544–547 (2011). https://doi.org/10.1016/j.wear.2010.04.010
Jiang, X.Q., Blunt, L., Stout, K.J.: Development of a lifting wavelet representation for surface characterization. Proc. R. Soc. Lond. A. 456, 2283–2313 (2000)
Monkova, K., et al.: Condition monitoring of Kaplan turbine bearings using vibro-diagnostics. Int. J. Mech. Eng. Robot. Res. 9(8), 1182–1188 (2020). https://doi.org/10.18178/ijmerr.9.8.1182-1188
Brown, C.A., et al.: Multiscale analyses and characterizations of surface topographies. CIRP Ann. 67(2), 839–862 (2018)
Berladir, K.V., Hovorun, T.P., Sviderskiy, V.A., Rudenko, P.V., Vyshehorodtseva, M.E.: Nanostructural modification of polytetrafluoroethylene and its composition by energy influence. J. Nano- Electron. Phys. 8(1), 01033–1–01033–5 (2016). https://doi.org/10.21272/jnep.8(1).01033
Pawlus, P., Reizer, R., Wieczorowski, M.: Functional importance of surface texture parameters. Materials 14(18), 5326 (2021). https://doi.org/10.3390/ma14185326
Acknowledgment
The research was partially supported by the Polish National Agency for Academic Exchange within the project “Strengthening the scientific cooperation of the Poznan University of Technology and Sumy State University in the field of mechanical engineering” (agreement no. BPI/UE/2022/8–00). Also, this research was partially supported by the Slovak Research and Development Agency within the project SK-UA-21–0060 and the Ministry of Education, Science, Research and Sport of the Slovak Republic within the project VEGA 1/0268/22.
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Wieczorowski, M., Trojanowska, J., Sokolov, O. (2023). Digital and Information Technologies in Metrology 4.0. In: Ivanov, V., Trojanowska, J., Pavlenko, I., Rauch, E., Piteľ, J. (eds) Advances in Design, Simulation and Manufacturing VI. DSMIE 2023. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-32767-4_8
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