Abstract
The development of a new methodology for the search and use of scientific and technical information from a wide class of electronic resources to improve the design efficiency of new models, modifications, and implementations of technical products is proposed. Verification of the possibilities for achieving the tactical and technical characteristics of scientific and technical products is conducted through virtual experiments as recommended in the scientific and technical literature and the documentation of innovations. To implement effective search, it is proposed to create an information system for the continuous monitoring of scientific journals, patents, sites of manufacturers of components, materials, and so on. A schematic diagram of the information system for searching for scientific and technical information is presented. A fragment of an information and search system based on a microservice architecture is shown.
REFERENCES
Binder, C., Neureiter, C., and Lüder, A., Towards a domain-specific information architecture enabling the investigation and optimization of flexible production systems by utilizing artificial intelligence, Int. J. Adv. Manuf. Technol., 2022, vol. 123, nos. 1–2, pp. 49–81. https://doi.org/10.1007/s00170-022-10141-2
Schluse, M. and Rossmann, J., From simulation to experimentable digital twins: Simulation-based development and operation of complex technical systems, 2016 IEEE Int. Symp. on Systems Engineering (ISSE), Edinburgh, Scotland, 2016, IEEE, 2016, pp. 273–278. https://doi.org/10.1109/syseng.2016.7753162
Qi, Q., Tao, F., Zuo, Yi., and Zhao, D., Digital twin service towards smart manufacturing, Procedia CIRP, 2018, vol. 72, pp. 237–242. https://doi.org/10.1016/j.procir.2018.03.103
Grieves, M., Digital twin certified: Employing virtual testing of digital twins in manufacturing to ensure quality products, Preprints.org, 2023, p. 2023051758. https://doi.org/10.20944/preprints202305.1758.v1
Alam, K.M. and El Saddik, A., C2PS: A digital twin architecture reference model for the cloud-based cyber-physical systems, IEEE Access, 2017, vol. 5, pp. 2050–2062. https://doi.org/10.1109/access.2017.2657006
Negri, E., Fumagalli, L., and Macchi, M., A review of the roles of digital twin in CPS-based production systems, Procedia Manuf., 2017, vol. 11, pp. 939–948. https://doi.org/10.1016/j.promfg.2017.07.198
IEC 62890:2020: Life-cycle management for systems and products used in industrial-process measurement, control and automation, International Electrotechnical Commission, 2020.
Binder, C., Polanec, K., Brankovic, B., Neureiter, C., Lastro, G., and Lüder, A., Enabling model-based requirements engineering in a complex industrial System of Systems environment, 2021 26th IEEE Int. Conf. on Emerging Technologies and Factory Automation (ETFA), Vasteras, Sweden, 2021, IEEE, 2021, pp. 1–6. https://doi.org/10.1109/etfa45728.2021.9613700
Shvedenko, V.N., Shchekochikhin, O.V., and Sinkevich, Y.A., A methodology of constructing a distributed information system for searching for scientific and technical information based on an object data model, Autom. Doc. Math. Linguist., 2020, vol. 54, no. 5, pp. 243–249. https://doi.org/10.3103/s0005105520050039
Manning, C., Raghavan, P., and Schutze, H., Introduction to Information Retrieval, Cambridge: Cambridge Univ. Press, 2008. https://nlp.stanford.edu/IR-book/ html/htmledition/irbook.html. Cited May 19, 2023.
Chi, T., Tezuka, T., Oyama, S., Tajima, K., and Tanaka, K., Web search improvement based on proximity and density of miltiple keywords, 22nd Int. Conf. on Data Engineering Workshops (ICDEW’06), Edinburgh, 2006, IEEE, 2006, p. x133. https://doi.org/10.1109/ICDEW.2006.164
Shen, D. and Lapata, M., Using semantic roles to improve question answering, Proc. 2007 Joint Conf. on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), Prague: Association for Computational Linguistics, pp. 12–21. https://aclanthology.org/D07-1002. Cited March 23, 2020.
Cheng, T., Lauw, H.W., and Paparizos, S., Entity synonyms for structured web search, IEEE Trans. Knowl. Data Eng., 2012, vol. 24, no. 10, pp. 1862–1875. https://doi.org/10.1109/tkde.2011.168
Yu, K. and Huang, G., Exploring consumers’ intent to use smart libraries with technology acceptance model, Electron. Libr., 2020, vol. 38, no. 3, pp. 447–461. https://doi.org/10.1108/el-08-2019-0188
Nelson, M.L., Harrison, T.L., and Rocker, J., OAI and NASA’s scientific and technical information, Libr. Hi Tech, 2003, vol. 21, no. 2, pp. 140–150. https://doi.org/10.1108/07378830310479785
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
The authors declare that they have no conflicts of interest.
About this article
Cite this article
Shvedenko, V.N., Shchekochikhin, O.V., Sinkevich, Y.A. et al. Features of Automation of Information Search in the Design of Technical Objects Using Their Digital Twins. Autom. Doc. Math. Linguist. 57, 145–155 (2023). https://doi.org/10.3103/S0005105523030081
Received:
Published:
Issue Date:
DOI: https://doi.org/10.3103/S0005105523030081