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Identification and evaluation of Industry 4.0 solutions in the automotive industry - a case study

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Purpose: The aim of this paper is to identify and evaluate the benefits of existing solutions in the field of Industry 4.0 in automotive companies in the sector of small and medium enterprises. Design/methodology/approach: The author applied the literature review to extract the main elements of Industry 4.0, which are adopted in the automotive industry. The next part was an interview with managers of a selected automotive company. The interview was analyzed using qualitative content analysis. Findings: Based on the assessment of implementing Industry 4.0 solutions in an enterprise from the SME sector, it can be concluded that a company may achieve many benefits thanks to such elements as automated machines, cyber-physical systems, big data and cloud-based tools. The results of these studies have shown that the efficient use of technology can significantly increase the productivity of a production company. Research limitations/implications: Industry 4.0 is developed intensively, but is still at an early stage of implementation. The research was based on a case study, which limits the generalization of results. In the future, the scope of research should be extended to the entire industry. Practical implications: Managers should analyze and use the innovative solutions that Industry 4.0 gives to achieve benefits in various areas of the company’s operations. Despite this, some activities in the production process are performed better by a human than a machine or an IT system. Originality/value: The article is one of a few that examine the implementation of Industry 4.0 solutions in the context of SMEs in Poland.
Rocznik
Tom
Strony
53--64
Opis fizyczny
Bibliogr. 26 poz.
Twórcy
  • University of Opole, Poland
Bibliografia
  • 1. Annunziata, M., and Evans, P.C. (2012). Industrial internet: Pushing the boundaries of minds and machines. General Electric, 26.
  • 2. Barenji, R.V., Akdag, Y., Yet, B., and Oner, L. (2019). Cyber-Physical-based PAT (CPbPAT) Framework for Pharma 4.0. International Journal of Pharmaceutics, 567:118445.
  • 3. Beier, G., Ullrich, A., Niehoff, S., Reißig, M., and Habich, M. (2020). Industry 4.0: How it is defined from a sociotechnical perspective and how much sustainability it includes: A literature review. Journal of Cleaner Production, Vol. 259, pp. 1-13.
  • 4. Bigliardi, B., Bottani, E., and Casella, G. (2020). Enabling technologies, application areas and impact of industry 4.0: A bibliographic analysis. Procedia Manufacturing, Vol. 42, pp. 322-326.
  • 5. Doshi, A., Smith, R.T., Thomas, B.H., and Bouras, C. (2017). Use of projector based augmented reality to improve manual spot-welding precision and accuracy for automotive manufacturing. The International Journal of Advanced Manufacturing Technology, Vol. 89, Iss. 5-8, pp. 1279-1293.
  • 6. Ghobakhloo, M. (2018). The future of manufacturing industry: a strategic roadmap toward Industry 4.0. Journal of Manufacturing Technology Management, Vol. 29, Iss. 6, pp. 910-936.
  • 7. Gorecky, D., Schmitt, M., Loskyll, M. and Zuhlke, D. (2014), Human-machine-interaction in the industry 4.0 era. Proceedings of IEEE International Conference on Industrial Informatics (INDIN), Porto Alegere.
  • 8. Gubbi, J., Buyya, R., Marusic, S., and Palaniswami, M. (2013). Internet of Things (IoT): a vision, architectural elements, and future directions. Future Generation Computer Systems. Vol. 29, Iss. 7, pp. 1645-1660.
  • 9. Hermann, M., Pentek, T., and Otto, B. (2016). Design Principles for Industrie 4.0 Scenarios. 49th Hawaii International Conference on System Sciences. Koloa: HI, pp. 3928-3937.
  • 10. Horváthová, R., Lacko, R., and Hajduová, Z. (2019). Using Industry 4.0 Concept – Digital Twin – to Improve the Efficiency of Leather Cutting in Automotive Industry. Quality Innovation Prosperity, Vol. 23, Iss. 2, pp. 1-12.
  • 11. Kagermann, H., Wahlster, W., and Helbig, J. (2013). Recommendations for implementing the strategic initiative Industrie 4.0 – final report of the Industrie 4.0 working group. Frankfurt: Communication Promoters Group of the Industry – Science Research.
  • 12. Kasabov, E. (2015). Start-up difficulties in early-stage peripheral clusters: the case of IT in an emerging economy. Entrepreneurship Theory and Practice, Vol. 39, Iss. 4, pp. 727-761.
  • 13. Lima, F., Nogueira de Carvalho, C., Acardi, M.B.S., and Gomes dos Santos, E. (2019). Digital manufacturing tools in the simulation of collaborative robots: towards Industry 4.0. Brazilian Journal of Operations & Production Management, Vol. 16, pp. 261-280.
  • 14. Lin, D., Lee, C.K.M., Lau, H., and Yang, Y. (2018). Strategic response to Industry 4.0: an empirical investigation on the Chinese automotive industry. Industrial Management & Data Systems, Vol. 118, Iss. 3, pp. 589-605.
  • 15. Lu, Y. (2017). Industry 4.0: A survey on technologies, applications and open research issues. Journal of Industrial Information Integration, Vol. 6, pp. 1-10.
  • 16. Miśkiewicz, R. (2019). Industry 4.0 in Poland – selected aspects of its implementation. Scientific Papers of Silesian University of Technology. Organization and Management Series 136, pp. 403-413.
  • 17. Müller, J.M. (2019). Business model innovation in small- and medium-sized enterprises: Strategies for industry 4.0 providers and users. Journal of Manufacturing Technology Management, Vol. 30, Iss. 8, pp. 1127-1142.
  • 18. Müller, J.M., Kiel, D., and Voigt, K.I. (2018). What drives the implementation of Industry 4.0? The role of opportunities and challenges in the context of sustainability. Sustainability, Vol. 10, Iss. 1, pp. 247-271.
  • 19. Restecka, M., and Wolniak, R. (2016). IT system in AID of welding processes quality management in the automotive industry. Archives of Metallurgy and Materials, Vol. 61, Iss. 4, pp. 1785-1792.
  • 20. Sarvankar, S.G., and Yewale, S.N. (2019). Additive Manufacturing in Automobile Industry. International Journal of Research in Aeronautical and Mechanical Engineering. Vol. 7, Iss. 4, pp. 1-10.
  • 21. Tong, S., and Lim, W. (2016). Made in China 2025: A Grand Industrial Ambition., Singapore: East Asian Institute, National University of Singapore.
  • 22. Vyshnevskyi, O., Liashenko, V., and Amosha, O. (2019). The impact of Industry 4.0 and AI on economic growth. Scientific Papers of Silesian University of Technology. Organization and Management Series, 140, pp. 391-400.
  • 23. Wang, Y., Ma, H., Yang, J., and Wang, K. (2017). Industry 4.0: a way from mass customization to mass personalization production. Advanced in Manufacturing, Vol. 5, pp. 311-320.
  • 24. Wolniak, R. (2019). Downtime in Automotive Industry Production Process – Cause Analysis. Quality Innovation Prosperity, Vol. 2, Iss. 2, pp. 101-118.
  • 25. Yin, R.K. (2009). Case Study Research: Design and Methods. California: Sage, Thousand Oacs.
  • 26. Yin, Y., Stecke, E., and Li, D. (2018). The evolution of production systems from Industry 2.0 through Industry 4.0. International Journal of Production Research, Vol. 56, Iss. 1-2, pp. 848-861.
Typ dokumentu
Bibliografia
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