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Study of the Vision System’s Impact on Increasing the Reliability of the Production System

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The purpose of the paper is to present the validity of the investment of a production plant in the development of production automation. The optimal use of production lines is the way to achieve the right return on investment and profits. Any unplanned stops reduce profitability of production and do not allow to achieve high production output. The introduction of various types of safety devices and process automation allows to prevent unwanted events. In particular, relieving employees of their responsibility and thus avoiding breakdowns caused by operator error can lead to an effective increase in Overall Equipment Effectiveness (OEE).The publication presents a study of the impact of the use of a vision system on increasing the reliability of the production system. As a result, an effective vision system based on a 3D sensor has been developed, which protects the production line against collision of the robot's chuck plate with final products, thus not leading to the collision and destruction of the robot's tools. The camera has been implemented in the robot's control system, which excludes the need to change the settings, because the necessary change of work parameters is made automatically via the communication interface, thus making the work easier for employees when retooling the production machine between orders. Increasing the Overall Equipment Effectiveness and high level of Return Of Investment (ROI) allow for an unequivocal decision on the importance of the investment decision. The financial expense allowed for increasing the efficiency and productivity of production line, which contributes to the growth of the company's competitiveness. The predictability of lead time has been significantly improved, which led to an increase in customer satisfaction.
Słowa kluczowe
Rocznik
Strony
46--56
Opis fizyczny
Bibliogr. 25 poz., rys., tab.
Twórcy
autor
  • Silesian University of Technology, ul. Akademicka 2A 44-100 Gliwice, Poland
  • Silesian University of Technology, ul. Akademicka 2A 44-100 Gliwice, Poland
Bibliografia
  • 1.Banas, W., Nalepa, B. (2017) Recognition of Text Commands and Control of the Mobile Robot Starter Kit 2.0. Mechatronics 2017 – Ideas for Industrial Applications, pp 10-19
  • 2.Canny, J. (1986). A Computional Approach to Edge Detection. IEEE Transactions on Pattern Analysis and Macine Intelligence, Vol. 8, No. 6, 1986.
  • 3. Coetzee, L., Botha, E., C. (1993) Fingerprint recognition in low quality images. Pattern Recognition, Vol. 26, pp 1441-1460.
  • 4. He, Y., Zheng, Y., Zhao, Y., Ren, Y., Lian, J., Gee, J. (2017). Retinal Image Denoising via Bilateral Filter with a Spatial Kernel of Optimally Oriented Line Spread Function.Comput Math Methods Med.
  • 5. Hetmanczyk, M. and Michalski, P. (2013) The Aid of a Mistake Proofing with the use of Mechatronic Systems According to the Poka-Yoke Methodology, Advanced Materials Research, 2014 Vol. 837, pp. 399-404
  • 6. IFM electronic GmbH O3D301 software manual (2017). https://www.ifm.com/mounting/706395UK.pdf [Accessed 05 June 2019].
  • 7. IFM electronic GmbH O3D301 operating instructions (2018). https://www.ifm.com/mounting/706397UK.pdf [Accessed 05 June 2019].
  • 8. IFM electronic GmbH O3D301 software manual (2018). https://www.ifm.com/mounting/7391233UK.pdf [Accessed 05 June 2019].
  • 9. Ivanov, D., Tabachinikov, S. (2019). The Six Circles Theorem revisited. https://www.math.psu.edu/tabachni/prints/Circles.pdf [Accessed 06 June 2019].
  • 10. Lankton, S., Tannenbaum, A. (2008). Localizing Region-Based Active Contours. IEEE Trans Image Process. Nov: 17(11), 2029-2039.
  • 11. Michalski, P. (2016). Czujniki przemysłowe XXI wieku, kierunki rozwoju a oczekiwania klientów, [online] Volume 1/2016, p. 42-44. Available at: https://emtsystems.pl/images/czujniki_przemyslowe_xxi_wieku.pdf [Accessed 01 June 2019]
  • 12. Michalski, P. (2018). Collecting data from industrial sensors in case of 4-th industrial revolution. IOP Conf. Ser.: Mater. Sci. Eng. 2018, vol. 400
  • 13. Michalski, P. and Hetmanczyk, M. (2015). Implementation of the safety components base on industrial networks. IOP Conf. Ser.: Mater. Sci. Eng. 2015, vol. 95
  • 14. Michalski, P. (2019). Advantages of Using Industrial Sensor Interfaces at the Machine Design Stage. In: Świder J., Kciuk S., Trojnacki M., ed., Mechatronics 2017 – Ideas for Industrial Applications. MECHATRONICS 2017. Advances in Intelligent Systems and Computing, vol. 934. Springer, pp. 308-313
  • 15. Nalepa, B., Gwiazda, A., Banas, W. (2018) Investigation of movement of mobile robot work. IOP Conference Series: Materials Science and Engineering, Vol. 400
  • 16. OpenCV documentation (2019). https://docs.opencv.org/ref/2.4.13/ [Accessed 06 June 2019].
  • 17. PMDSKD2 documentation (2019).
  • 18. https://support.bluetechnix.at/wiki/PMDSDK_/_PMDMDK_User_Manual [Accessed 06 June 2019].
  • 19. SICK AG UM30 documentation (2018).https://cdn.sick.com/media/docs/6/06/206/Operating_instructions_UM30_21_111_UM30_21_115_de_en_IM0032206.PDF [Accessed 03 June 2019].
  • 20. SICK AG PIM60 quick start guide (2017).https://cdn.sick.com/media/docs/5/35/835/quickstart_Inspector_PIM60_de_en_fr_zh_it_es_IM0048835.PDF [Accessed 04 June 2019].
  • 21. SICK AG PIM60 operating instruction (2018).https://cdn.sick.com/media/docs/6/36/836/Operating_instructions_Inspector_PIM60_ver_2.0_en_IM0048836.PDF [Accessed 04 June 2019].
  • 22. SICK AG PIM60 reference manual (2018). https://cdn.sick.com/media/docs/6/16/316/User_manual_Inspector_PIM60_ver_2.0_en_IM0081316.PDF [Accessed 04 June 2019].
  • 23. Stevenhagen, P. (2019). Number Rings. http://websites.math.leidenuniv.nl/algebra/ant.pdf [Accessed 06 June 2019].
  • 24. Tan, T., He, Z., Sun, Z. (2010) Efficient and robust segmentation of noisy iris images for non-cooperative iris recognition. Image and Vision Computing, Vol. 28, pp 223-230.
  • 25. Yoruk, E., Konukoglu, E., Sankur, B., Darbon, J. (2006) Shape-based hand recognition.Transactions on Image Processing, Vol. 15, pp 1803-1815.
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-c0d4b5e1-4b85-41bb-9c87-bd980fb334fd
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