Current volume

Digital Twin in Metrology: Opportunities, Current Implementations and Research Challenges

Metrology & Hallmark

Authors Małgorzata Poniatowska (Białystok University of Technology), Dariusz Mazurkiewicz (Lublin University of Technology), Piotr Sobecki (Central Office of Measures, National Information Processing Institute)

Abstract

Digital twin (DT) technology is now popular in several research and development applications, including also metrology. Measurements as a source of data play an important role not only in DT design, modelling and implementation, but digital twins of measurement systems can also be successfully used in many applications, for example to estimate measurement uncertainty. The digital twin method has a tremendous potential and many application possibilities in metrology, therefore in this paper some up-to-date research results in this area are presented and discussed, including some representative activities of National Metrology Institutes (NMIs).

Bibliography

[1] Wright L., Davidson S., How to tell the difference between a model and a digital twin. Advanced Modeling and Simulation in Engineering Sciences 2020, 7, 13, https://doi.org/10.1186/s40323-020-00147-4.
[2] West T, Blackburn M. Is digital thread/digital twin affordable? A systemic assessment of the cost of DoD’s latest Manhattan project. In: Complex adaptive systems, Chicago, USA, 2017.
[3] Digital Twin—looking behind the buzzwords, April 2018 edition of benchmark magazine. https://www.nafems.org/publications/benchmark/archive/april-2018/.
[4] Vlaeyen M., Haitjema H., Dewulf W., Digital Twin of an Optical Measurement System. Sensors 2021, 21, 6638, https://doi.org/10.3390/s21196638.
[5] Stojadinovic S.M., Majstorovic V.D., Durakbasa N.M., An approach to development of the digital inspection twin based on CMM. Measurement, Sensors 2021, 18, https://doi.org /10.1016/j.measen.2021.100300.
[6] Stojadinovic S.M., Majstorovic V.D., Durakbasa N.M., Stanic D., Contribution to the development of a digital twin based on CMM to support the inspection process. Measurement, Sensors 2022, 22, https://doi.org/10.1016/j.measen.2022.100372.
[7] Marjanovic M.A., Stodijanovic S.M., Zivanovic S., Modelling and Simulating the Digital Measuring Twin Based on CMM. Modelling 2023, 4, https://doi.org/10.3390/modelling4030022.
[8] Poole A., Sutcliffe M., Pierce G., Gachagan A., Autonomous, Digital-Twin Free Path Planning and Deployment for Robotic NDT: Introducing LPAS: Locate, Plan, Approach, Scan Using Low Cost Vision. Sensors 2022, https://doi.org/10.3390/app12105288.
[9] Tang Y., Wang Y. A Digital Twin-Based Intelligent Robotic Measurement System for Freeform Surface Parts. in: IEEE Transactions on Instrumentation and Measurement 2023, 72, https://doi.org/10.1109TIM.2023.3261933.
[10] Zangl K., Danzl R., Kreil M., Helmli F., High-precision optical coordinate metrology for punching tools by
using a digital twin for the measurement strategy. Proceedings Volume 12098, Dimensional Optical Metrology and Inspection for Practical Applications XI; 12098 0 4 (2022), https://doi.org/10.1117/12.2618469.
[11] Moroni G., Petro S., Geometric Inspection Planning as a Key Element in Industry 4.0. Proceedings of 3rd International Conference on the Industry 4.0 Model for Advanced Manufacturing. AMP 2018, 293-310.
[12] Anagnostakis D., Ritchie J., Lim T., Sung R., Dewar R. A Virtual CMM Inspection Tool for Capturing Planning Strategies. In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference DETC2017- 67519, American Society of Mechanical Engineers 2017, https://doi.org/10.1115/DETC2017-67519.
[13] Poniatowska M. Deviation model based method of planning accuracy inspection of free-form surfaces
using CMMs. Measurement 2012, 45, https://doi.org/10.1016/j.measurement.2012.01.051.
[14] Gohari H., Berry C., Barari A., A Digital Twin for Integrated Inspection System in Digital Manufacturing. IFAC PapersOnline 2019, 52, 10, https://doi.org/10.1016/j.ifacol.2019.10.020.
[15] Ahmed Y., S., ElMaraghy H., Offline digital twin for simulation and assessment of product surface quality.
International Journal of Advanced Manufacturing Technology 2023, 127, https://doi.org/10.1007/
s00170-023-11662-0.
[16] Wärmefjord K., Söderberg R., Lindkvist L., Lindau B., Carlson J. S., Inspection Data To Support A Digital Twin For Geometry Assurance. Proceedings Of The ASME International Mechanical Engineering Congress And Exposition 2017, 2, https://doi.org/10.1115/IMECE2017-70398.
[17] Söderberg R., Wärmefjord K., Carlson J. S., Lindkvist L., Towards a Digital Twin for Real-time Geometry
Assurance in Individualized Production. CIRP Annuals of Manufacturing Technology 2017, 66, https://doi.org/10.1016/j.cirp.2017.04.038.
[18] Poroskun I., Rothleitner Ch., Heißelman D., Structure of digital metrological twins as software for uncertainty estimation. Journal of Sensors and Sensor Systems 2022, 11, https://doi.org/10.5194/jsss-11-75-2022.
[19] Sładek, J., Gąska, A., Evaluation of coordinate measurement uncertainty with use of virtual machine
model based on Monte Carlo method. Measurement 2012, 45, ht tps://doi.org /10.1016/j.
measurement.2012.02.020.
[20] Gąska A., Gąska P., Gruza, M., Simulation Model for Correction and Modeling of Probe Head Errors in
Five-Axis Coordinate Systems. Applied Sciences 2012, 6, https://doi.org/10.3390/app6050144.
[21] Gąska A., Harmatys W., Gąska P., Gruza M., Gromczak K., Ostrowska K., Virtual CMM-based model for uncertainty estimation of coordinate measurements performed in industrial conditions. Measurement 2017, 98, https://doi.org/10.1016/j.measurement.2016.12.027.
[22] Gąska A., Sładek J., Gąska P., Challenges for Uncertainty Determination in Dimensional Metrology Put by Industry 4.0 Revolution. In Proceedings of the 5th International Conference on the Industry 4.0 Model for Advanced Manufacturing, Belgrade, Serbia, 1–4 June 2020, 92–104.
[23] Hu Y., Yang Q., Design, Implementation, and Testing of Advanced Virtual Coordinate-Measuring Machines. IEEE Transactions on Instrumentation and Measurement 2012, 61, https://doi.org/10.1109/TIM.2011.2175828.
[24] Gąska P., Gąska A., Sładek J., Jędrzejewski J., Simulation model for uncertainty estimation of
measurements performed on five-axis measuring systems. International Journal of Advanced
Manufacturing Technology 2019, 118, https://doi.org/10.1007/s00170-019-04319-4.
[25] Sýkora J., Linkeová I., Skalník P., Freeform digital twin approach to develop the HP 300 freeform verification standard. Measurement 2013, 218, https://doi.org/10.1016/j.measurement.2023.113227.
[26] Schleich B., Wärmefjord K., Söderberg R., Wartzacka S., Geometrical Variations Management 4.0: towards
next Generation Geometry Assurance. Procedia CIRP 2018, 75, https://doi.org/10.1016/j.procir.2018.04.078.
[27] Tolio T.A.M., Monostori L., Vàncza J., Sauer O. Platform-based manufacturing. CIRP Annals 2023, 72, https://doi.org/10.1016/j.cirp.2023.04.091.
[28] Riaño C., Rodriguez E., Alvares, A. J., A Closed-Loop Inspection Architecture for Additive Manufacturing
Based on STEP Standard. IFAC-PapersOnLine 2019, 52 (13), https://doi.org/10.1016/j.ifacol.2019.11.629.
[29] Gaha R., Durupta A., Eynarda B., Towards the implementation of the Digital Twin in CMM inspection
process. Procedia Manufacturing 2021, 54, https://doi.org/10.1016/j.promfg.2021.07.033.
[30] Hedberg T. et al. Testing the digital thread in support of model-based manufacturing and inspection.
Journal of Computing and Information Science in Engineering 2016, 16, https://doi.org/10.1115/1.4032697.
[31] Schnürer D., Hammelmüller F., Holl H. J., Kunze W., Offline digital twin synchronization using measurement data and machine learning methods. Materials Today: Proceedings 2022, 62, https://doi.
org/10.1016/j.matpr.2022.02.566.
[32] Da Rocha H., Pereira J., Abrishambaf R., Espirito Santo A. An Interoperable Digital Twin with the IEEE 1451 Standards. Sensors 2022, 22, https://doi.org/10.3390/s22197590.
[33] Zhang R., Wang F., Cai J., Wang Y., Guo H., Zheng J., Digital twin and its applications: A survey. International Journal of Advanced Manufacturing Technology 2022, 123, https://doi.org/10.1007/
s00170-022-10445-3.
[34] Khan T. H, Noh C., Han S. H., Correspondence measure: a review for the digital twin standardization.
International Journal of Advanced Manufacturing Technology 2023, 128, https://doi.org/10.1007/
s00170-023-12019-3.
[35] Lehmann J., Schorz S., Rache A., Häußermann T., Rädle M., Reichwald J. Establishing Reliable Research
Data Management by Integrating Measurement Devices Utilizing Intelligent Digital Twins. Sensors 2023, 23, https://doi.org /10.10 07/s00170-022-10445-3.
[36] Bohlin R., Hagmar J., Bengtsson K., Lindkvist L., Carlson J.S., Söderberg R., Data Flow and Communication Framework Supporting Digital Twin for Geometry Assurance. Proceedings of the ASME 2017 International Mechanical Engineering Congress and Exposition. Volume 2: Advanced Manufacturing. Tampa, Florida, USA. November 3–9, 2017, ASME, https://doi.org/10.1115/IMECE2017-71405.
[37] Lowenstein D., Mueth Ch., Implementing a Digital Twin, Design and Test, Test and Measurement
Strategy. 65th IEEE Autotestcon Conference 2022, https://doi.org/10.1109/AUTOTESTCON47462.2022.9984739.
[38] De Paolis L.T., De Luca V., Paiano R. Sensor data collection and analytics with Thingsboard and Spark
streaming. Proc. IEEE Workshop Environ., Energy, Struct. Monit. Systems 2018, 1–6, https://doi.org/10.1109/eesms.2018.8405822.
[39] Fei T., Bin X., Qinglin Q., Jianfeng C., Ping J., Digital twin modelling. Journal of Manufacturing Systems
2022, 64, 372-389, https://doi.org/10.1016/j.jmsy.2022.06.015.
[40] Mustapää T., Autiosalo J., Nikander P., Siegel J.E., Viitala R., Digital Metrology for the Internet of Things. 2020 Global Internet of Things Summit (GIoTS), Dublin, Ireland, 2020, 1-6, https://doi.org/10.1109/GIOTS49054.2020.9119603.
[41] Mazurkiewicz D., Ren Y., Qian C., Novel Approach to Prognostics and Health Management to Combine
Reliability and Process Optimisation. In: Liu, Y., Wang, D., Mi, J., Li, H. (eds) Advances in Reliability and Maintainability Methods and Engineering Applications. Springer Series in Reliability Engineering. Springer, 2023, Cham. https://doi.org/10.1007/978-3-031-28859-3_23.
[42] Jasiulewicz-Kaczmarek M., Mazurkiewicz D., Wyczółkowski R. – Strategie i metody utrzymania
ruchu. PWE Warszawa 2023, ISBN: 978-83-208-2509-1.

Options

go up