RESEARCH OF DIKW AND 5C ARCHITECTURAL MODELS FOR CREATION OF CYBER-PHYSICAL PRODUCTION SYSTEMS WITHIN THE CONCEPT OF INDUSTRY 4.0
DOI:
https://doi.org/10.30837/ITSSI.2021.15.132Keywords:
Industry 4.0, Smart Manufacturing, Digital Twins, cyber-physical industrial systems, DIKW model, 5C architectureAbstract
The development of cyber-physical production systems is a complex scientific and technical task, therefore the developer needs to determine the requirements, tasks for the system being developed and choose an architectural model for its implementation. In turn, the choice of an architectural model assumes a balance for the set of requirements of persons interested in its development. In a typical case, the development of a specific cyber-physical industrial systems needs to be adapted to the means of implementation, to the realities of its future use, maintenance and evolution. Subject matter of this study are architectural models for building complex cyber-physical production systems. Goal of this article is a study of architectural models DIKW and 5C, according to the results of the decomposition of which, in the future, it will be possible to carry out a mathematical description of elementary problems of each level and their physical or simulation modeling. To achieve this goal, it is necessary to solve the following tasks: analyze the DIKW model; analyze the architectural model 5C; compare the DIKW model and the 5C architectural model, using its structural decomposition into levels, information and command channels with feedback within each structure. The research carried out is based on the methods of decomposition and formalized representation of systems. Conclusions: Based on the results of the decomposition at each structural level of the DIKW and 5C models, a decomposition structure was developed, which shows the main differences and general similarities of the models. It was revealed that the 5C model, as a common software shell that combines integrated sensors and actuators, is more suitable for solving problems of developing a cyber-physical production system, and the DIKW interpretation model is more suitable for solving problems of modifying existing systems at enterprises, and the choice of the model itself the development of a cyber-physical production system depends on the requirements of the customer, existing equipment, the level of its automation and the level of project financing.
References
Sony, M., Naik, S. (2019), "Key ingredients for evaluating Industry 4.0 readiness for organizations: a literature review", Benchmarking: An International Journal, Vol. 27, No. 7, P. 2213–2232. DOI: https://doi.org/10.1108/BIJ-09-2018-0284
Rossit, D. A., Tohmé, F., Frutos, M. (2019), "Industry 4.0: smart scheduling", International Journal of Production Research, No. 57 (12), P. 3802–3813. DOI: https://doi.org/10.1080/00207543.2018.1504248
Holdren, J. P., Power, T., Tassey, G., Ratcliff, A., Christodoulou, L. (2012), "A National strategic plan for advanced manufacturing", US National Science and Technology Council, Washington, DC., available at :: http://www.docin.com/p-391856652.html
Foresight, U. K. (2013), The future of manufacturing: a new era of opportunity and challenge for the UK, Summary Report, The Government Office for Science, London, 20 p.
Cohen, E. (2007), " Industrial Policies in France: The Old and the New", Journal of Industry, Competition and Trade, No. 7, P. 213–227. DOI: https://doi.org/10.1007/s10842-007-0024-8
Taki, H. (2017), "Towards Technological Innovation of Society 5.0", Journal-Institute of Electrical Engineers of Japan, No. 137 (5), P. 275–275. DOI: https://doi.org/10.1541/ieejjournal.137.275
Moon, H. C., Chung, J. E., Choi, S. B. (2018), "Koreaʼs Manufacturing Innovation 3.0 Initiative", Journal of Information and Management, No. 38 (1), P. 26–34. DOI: https://doi.org/10.20627/jsim.38.1_26
Zhou, J. (2015), "Intelligent mannfacturing-main direction of "made in china 2025", Zhongguo Jixie Gongcheng/China Mechanical Engineering, No. 26 (17), P. 2273–2284. DOI: https://doi.org/10.3969/j.issn.1004-132X.2015.17.001
Paulo Leitão, Armando Walter Colombo, Stamatis Karnouskos (2016), "Industrial automation based on cyber-physical systems technologies: Prototype implementations and challenges", Computers in Industry, Vol. 81, P. 11–25. DOI: https://doi.org/10.1016/j.compind.2015.08.004
Huang, G., Chen, J., Khojasteh, Y. (2021), "A cyber-physical system deployment based on pull strategies for one-of-a-kind production with limited resources", Journal of Intelligent Manufacturing, No. 32 (2), P. 579–596. DOI: https://doi.org/10.1007/s10845-020-01589-8
Stefano Zanero (2017), "Cyber-Physical Systems", Computer, Vol. 50, Issue 4, P. 14–16. DOI: https://doi.org/10.1109/MC.2017.105
Mosterman, P. J., Zander, J. (2016), "Cyber-physical systems challenges: a needs analysis for collaborating embedded software systems", Software & Systems Modeling, No. 15, P. 5–16. DOI: https://doi.org/10.1007/s10270-015-0469-x
Nevliudov, I., Yevsieiev, V., Demska, N., Novoselov, S. (2020), "Development of a software module for operational dispatch control of production based on cyber-physical control systems", Innovative Technologies and Scientific Solutions for Industries, No. 4 (14), P. 155–168. DOI: https://doi.org/10.30837/ITSSI.2020.14.155
Lee, J., Jin, C., Bagheri, B. (2017), "Cyber physical systems for predictive production systems", Production Engineering, Vol. 11, P. 155–165. DOI: https://doi.org/10.1007/s11740-017-0729-4
Sergeychik, A. (2019), "A step towards Industry 4.0: Festo devices for modern production" ["Shag navstrechu "Industrii 4.0": ustroystva Festo dlya organizatsii sovremennogo proizvodstva"], Control Engineering Rossiya, No. 4 (82), P. 38-41.
Sosnin, P. I. (2008), Architectural modeling of automated systems [Arkhitekturnoye modelirovaniye avtomatizirovannykh sistem], Ul'yanovsk, UlGTU, 147 р.
Lee, J., Davari, H., Singh, J., Pandhare, V. (2018), "Industrial artificial intelligence for industry 4.0-based manufacturing systems", Manufacturing Letters, No. 18, P. 20–23. DOI: https://doi.org/10.1016/j.mfglet.2018.09.002
Jiang, J. (2018), "An improved cyber-physical systems architecture for industry 4.0 smart factories", Advances in Mechanical Engineering, No. 10 (6). DOI: https://doi.org/10.1177/1687814018784192
Erasmus, J., Vanderfeesten, I., Traganos, K., Keulen, R., Grefen, P. (2020), "The HORSE project: The application of business process management for flexibility in smart manufacturing", Applied Sciences (Switzerland), No. 10 (12). DOI: https://doi.org/10.3390/APP10124145
Beskorovainyi, V. (2020), "Combined method of ranking options in project decision support systems", Innovative Technologies and Scientific Solutions for Industries, No. 4 (14), P. 13–20. DOI: https://doi.org/10.30837/ITSSI.2020.14.013
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