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Concept of reconfigurability in interoperation manufacturing buffers for smart factory

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this article, it is described how the reconfigurable inter-operational buffers system built on the Digital Twin platform. Interoperating production buffers are now widely used in production. Their effect on the production system can be seen in decreasing downtime. From a cost-based point of view, the interoperating production buffers may generate a gain from the reduction in the volume of work-in-process, with which we increase production performance. This ratio depends on the average number of products that the buffers contain. The average number of pieces in the buffer is limited by the capacity of the buffer. The impact of turbulence in production is seen precisely on the average content of inter-operational production buffers. If we want to maintain work-in-process on optimal values, it is necessary to calculate and maintain the optimal capacity of each interoperating production buffer on the line. In the context of Smart Factory, it is currently possible that the current capacity of the interoperating production buffers is maintained according to the current state of production. In the subject system, real production facilities communicate with each other through the IoT as autonomous agents, which are decided on the basis of a formula to calculate the optimal capacity of the buffers, the prediction of faults and negotiation, thus actively maintaining the optimal capacity of intermediate operating production buffers for Smart Factory support.
Wydawca
Rocznik
Strony
575--582
Opis fizyczny
Bibliogr. 17 poz., rys.
Twórcy
  • University of Žilina, Faculty of Mechanical Engineering, Department of Industrial Engineering, Slovakia
  • University of Žilina, Faculty of Mechanical Engineering, Department of Industrial Engineering, Slovakia
  • University of Žilina, Faculty of Mechanical Engineering, Department of Industrial Engineering, Slovakia
  • University of Žilina, Faculty of Mechanical Engineering, Department of Industrial Engineering, Slovakia
  • University of Žilina, Faculty of Mechanical Engineering, Department of Industrial Engineering, Slovakia
Bibliografia
  • 1.Bubeník, P., 2004. A scheduling system for minimizing the costs of production. Strojniški vestnik : Journal of mechanical engineering, 50(5), 291-297. ISSN 0039- 2480.
  • 2.Bubeník, P., Horák, F., 2014. Proactive approach to manufacturing planning. Quality Innovation Prosperity, 18(1), 23-32. https://doi.org/10.12776/QIP.V18I1.208
  • 3.Dulina, L., Malcho, M., Micieta, B., 2003. Optimal utilization of the employees potention in the manufacturing condition, 14th International Symposium of the Danube-AdriaAssociation-for-Automation-and-Manufacturing, Sarajevo, 129-130.
  • 4.Gašová, M., Gašo, M., Štefánik, A., 2017. Advanced industrial tools of ergonomics based on Industry 4.0 concept. Procedia Engineering, 192, 219-224. ISSN 1877- 7058. https://doi.org/10.1016/j.proeng.2017.06.038
  • 5.Gregor, T., Krajčovič, M., Wiecek., D. 2017. Smart Connected Logistics. Procedia Engineering, 192, 265-270. ISSN 1877-7058. https://doi.org/10.1016/j.proeng.2017.06.046
  • 6.Gregor, M., Groumpos, P. P., Gregor, M., 2017. Using Weight Constraints and Masking to Improve Fuzzy Cognitive Map Models. 2nd Conference on Creativity in Intelligent Technologies and Data Science (CIT and DS), Volgograd, Russia, SPRINGERVERLAG BERLIN : Communications in Computer and Information Science, 91-106.
  • 7.Jankalová, M., Jankal, R., 2018. Sustainability Assessment According to the Selected Business Excellence Models. Sustainability, 10(10: 3784), https://doi.org/10.3390/su10103784
  • 8.Kolarovszki, P., Vaculik, J., 2014. Intelligent storage system based on automatic identification. TRANSPORT AND TELECOMMUNICATION JOURNAL, 15(3), 185- 195. https://doi.org/10.2478/ttj-2014-0016
  • 9.Krajčovič, M., Plinta, D., 2013. Adaptive inventory control system for material items with continuous non-stationary demand. Management and production engineering review, 5(1), 1-20, https://doi.org/10.2478/mper-2014-0002
  • 10.Maixner, L., 1980 Navrhovanie automatických výrobných systémov, SNTL – Nakladatelství technické literatúry, Praha.
  • 11.Mičieta, B., Ďurica, L., Biňasová, V., 2018. New solution of abstract architecture for control and coordination decentralized systems. Tehnički Vjesnik. 25(1), 135-143. ISSN 1330-3651, https://doi.org/10.17559/TV-20160117100949
  • 12.Mičieta, B., Edl, M., Krajčovič, M., Dulina, Ľ., Bubeník, P., Ďurica, L., Biňasová, V., 2018. Delegate MASs for coordination and control of one-directional AGV systems: a proof-of-concept. The International Journal of Advanced Manufacturing Technology, 94(1-4), 415-431. ISSN 0268-3768.
  • 13.Mleczko, J., Dulina, Ľ., 2014. Manufacturing documentation for the high-variety products. Management and production engineering review, 5(3), 53-61. ISSN 2082- 1344. https://doi.org/10.2478/mper-2014-0027
  • 14.Mozol, Š., 2018. Určenie kapacít výrobných zásobníkov vo vybranom podniku. diploma thesis. Žilina : Žilinská univerzita v Žiline, 2018. 69 pp.
  • 15.Ristvej, J., Zagorecki, A.T., Holla, K., et al., 2013. Modelling, simulation and information systems as a tool to support decision-making process in crisis management. European Simulation and Modelling Conference (ESM 2013), Lancaster, 71-76.
  • 16.Wolniak, R., Skotnicka-Zasadzień, B., Gębalska-Kwiecień, A., 2018. Identification of bottlenecks and analysis of the state before applying lean management. 12th International Conference Quality Production Improvement (QPI 2018), Zaborze, Poland, 1-6,
  • 17.Yang, H.L., Chang, T.W., Choi, Y., 2018. Exploring the Research Trend of Smart Factory with Topic Modeling. Sustainability 10(8: 2779), https://doi.org/10.3390/su10082779
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7cb55161-7e4c-46f8-bd5e-ce0956b2c08d
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