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Production Line Modelling in Accordance with the Industry 4.0 Concept as an Element of Process Management in the Iron and Steel Industry

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Języki publikacji
EN
Abstrakty
EN
Simulations are becoming one of the most important techniques supporting production preparation, even in those industrial sectors with atypical technological processes, such as in metallurgy, where there is a multiphase material flow. This is due to the fact that in the conditions of a market economy, enterprises have to solve more and more complex problems in a shorter time. On the basis of the existing production process and the knowledge of the flow characteristics in a given process, a model is built, which, when subjected to simulation tests, provides experimental results in the scope of the defined problem. The use of computer techniques also creates new possibilities for the rational use of the reserves inherent in each technological process. Taking into account the existing demand and the state of modern technology, the computer model can be a source of information for further analysis and decision-making processes supporting company management. At work a model of the logistic system was made on the example of a hot-rolled steel strip mill, on which simulation experiments were carried out to improve the effectiveness and efficiency of the analysis production line. The presented article aims to disseminate the idea of ??Industry 4.0 in Polish companies from the manufacturing industry sector, taking into account simulation techniques.
Słowa kluczowe
Twórcy
  • AGH University of Science and Technology, Faculty of Management, Poland, ul. Gramatyka 10, 30-067 Cracow, Poland
  • AGH University of Science and Technology, Faculty of Management, Poland
Bibliografia
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  • Bysko S., Krystek J., Bysko Sz. and Lenort R., (2019), Buffer management in solving a real sequencing problem in the automotive industry – Paint Shop 4.0 concept, Management and Production Engineering Review, vol. 29, no. 3, pp. 507–527. DOI: 10.24425/acs.2019.130203.
  • Cyfert S., Glabiszewski W. and Zastempowski M. (2021), Impact of Management Tools Supporting Industry 4.0 on the Importance of CSR during COVID-19. Generation Z, Energies, vol. 14, no. 6, pp. 1–13. DOI: 10.3390/en14061642.
  • Ershadi N.Y. and Menéndez J.M. (2017), Vehicle Tracking and Counting System in Dusty Weather with Vibrating Camera Conditions, Journal of Sensors, pp. 1–9, [online] DOI: 10.1155/2017/3812301 [access: 15/09/2020].
  • Gudanowska A. (2017), Transformation towards Industry 4.0 – identification of research trends and aspect of necessary competences in the light of selected publications, Research in Logistics & Production, vol. 7, no. 5, pp. 431–441. DOI: 10.21008/j.2083-4950.2017.7.5.4.
  • Hamrol A., Gawlik J. and Sładek J. (2019), Mechanical engineering in Industry 4.0, Management and Production Engineering Review, vol. 10, no. 3, pp. 4–28. DOI: 10.24425/mper.2019.129595.
  • Hansen D., Nasrollahi K. and Rasmusen C.B. (2017), Real-time barcode detection and classification using deep learning, Proceedings of the 9th International Joint Conference on Computational Intelligence, SCITEPRESS Digital Library, vol. 1, pp. 321–327, https://www.scitepress.org/Papers/2017/65082/65082.pdf, [access: 15/09/2020].
  • Kiepas A. (2018), Sustainable development with Industry 4.0 in prospect, Papers on Global Change, vol. 3, no. 25, pp. 44–55. DOI: 10.24425/igbp.2018.124891.
  • Kosacka-Olejnik M. (2019), Industry 4.0: state of the art and research implications, LogForum, vol. 15, no. 4, pp. 475–485. DOI: 10.1080/00207543.2018.1442945.
  • Kumar Mohd S., Asjad M. S. (2020), Industry 4.0: complex, disruptive, but inevitable, Management and Production Engineering Review, vol. 11, no 1, pp. 43–51. DOI: 10.24425/mper.2020.132942.
  • Lee C.K.M., Lv Y., Ng K.K.H. et al. (2018), Design and application of Internet of things-based warehouse management system for smart logistics, International Journal of Production Research, vol. 56, no. 8, pp. 2753–2768. [online], DOI: 10.1080/00207543.2017.1394592, [access: 15/09/2020].
  • Liszka K., Klimkiewicz K. and Malinowski P. (2019), Polish Foundry Engineer with Regard to Changes Carried by the Industry 4.0, Archives of Foundry Engineering, vol. 19, no. 1, pp. 103–108. DOI: 10.24425/afe.2019.127102.
  • Lola I. and Bakeev M. (2020), Pilot study of Industry 4.0 and digital technology prevalence in russian manufacturing companies, Management and Production Engineering Review, vol. 11, no. 3, pp. 26–37. DOI: 10.24425/mper.2020.134929.
  • Luscinski S. and Ivanov V. (2020), A simulation study of Industry 4.0 factories based on the ontology on flexibility with using FlexSim software, Management and Production Engineering Review, vol. 11, no. 3, pp. 74–83. DOI: 10.24425/mper.2020.134934.
  • Łukasik K. and Stachowiak T. (2020), Intelligent management in the age of Industry 4.0 – an example of a polymer processing company, Management and Production Engineering Review, vol. 11, no. 2, pp. 38–49. DOI: 10.24425/mper.2020.133727.
  • Mao J., Xing H. and Zhang X. (2018), Design of Intelligent Warehouse Management System, Wireless Personal Communications, vol. 102, no. 2, pp. 1355-1367.
  • Nguyen T., Zhou L. and Spiegler V. (2018), Big data analytics in supply chain management: A state-of-the-art literature review, Computers & Operations Research, vol. 98, pp. 254–264.
  • Niekurzak M. and Kubińska-Jabcoń E., (2014), Logistic system approach to the management and modelling of the metallurgical enterprise, Logistic, pp. 4630–4637.
  • Nogalski B. and Niewiadomski P. (2020), Industry 4.0 desiderata as micro foundations in the assessment of companies’ maturity – case study, Management and Production Engineering Review, vol. 11, no. 4, pp. 92– 103. DOI: 10.24425/mper.2020.136123.
  • Perzyk M., Dybowski B. and Kozłowski J. (2019), Introducing Advanced Data Analytics in Perspective of Industry 4.0 in a Die Casting Foundry, Archives of Foundry Engineering, vol. 19, no. 1, pp. 53–57. DOI: 10.24425/afe.2018.125191.
  • Rojek I., Macko M., Mikołajewski D., Sága M. and Burczyński T. (2021), Modern methods in the field of machine modelling and simulation as a research and practical issue related to industry 4.0, Bulletin of the Polish Academy of Sciences: Technical Sciences, vol. 69, no. 2, pp. 1–12. DOI: 10.24425/bpasts.2021.136717.
  • Ślusarczyk B. (2018), Industry 4.0: are we ready?, Polish Journal of Management Studies, vol. 17, no. 1, pp. 232–248. DOI: 10.17512/pjms.2018.17.1.19.
  • Taliaferro A., Guenette C. and Ankit Agarwal M.P., (2016), Industry 4.0 and Distribution Centers: Transforming Distribution Operations Through Innovation, Deloitte University Press, Brazil, [online], https://www2.deloitte.com/content/dam/insights/us/articles/3294_industry-4-0-distribution-centers/DUP_Industry-4-0-distribution-centers.pdf, [access: 05/09/2020].
  • Wyrzykowski W. (2020), Hot strip mill – materials of one of the Polish steel mills (unpublished documents 2018–2020).
  • Zawadzki P., Żywicki K. (2016), Smart Product Design and Production Control for Effective Mass Customization in the Industry 4.0 Concept, Management and Production Engineering Review, vol. 7, no. 3, pp. 105–112. DOI: 10.1515/mper-2016-0030.
  • Zhong R., Xu X., Klotz E. et al. (2017), Intelligent Manufacturing in the Context of Industry 4.0: A Review, Engineering, no. 5, vol. 3, pp. 616–630.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-de51f953-e5e1-4d7d-ad0c-04189aef3463
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