Charakterystyka procesu produkcji opon oraz ich defektów na przykładzie współczesnego przedsiębiorstwa

• Autorzy: Majewski Wojciech , Dostatni Ewa , Diakun Jacek

Identyfikatory

DOI

10.25961/ent.manag.25.01.02

Warianty tytułu

EN

Characteristics of the tire production process and their defects on the example of a modern enterprise

• Języki publikacji: PL

Abstrakty

EN

The article presents contemporary challenges faced by tire manufacturers. General trends in the development of the tire industry are outlined. The negative impact of rubber waste on the environment was emphasized. The production process of radial tires used in passenger cars is presented. The basic constructions of tires and the components used for their production are discussed. The meaning and functions of the tire components are presented. The flow of the production process has been described, including all its stages. The possibilities of modern VMI MAXX tire assembling machines were commented, and the tire assembling process was characterized in detail. Methods of routine tire quality control used in mass production are discussed. The values describing the uniformity of tires were characterized. The division of tire defects used in the tire industry is presented. The tools and methods for detecting tire defects were characterized. Contemporary trends in the elimination of tire defects have been identified, especially emphasizing the potential of methods based on the use of artificial intelligence. It was noted that a solution to reduce the amount of tire waste due to exceeding the uniformity limits is needed. Authors noticed new opportunities thanks to the modern technologies used to register the tire assembling process.

Słowa kluczowe

PL

produkcja opon; jednorodność opon; konstrukcja opony radialnej; uszkodzenia opon; montaż opon; produkcja masowa

EN

tire production; tire uniformity; radial tire construction; tire defects; tire assembling process; large-scale production

• Wydawca: Polskie Towarzystwo Zarządzania Produkcją
• Czasopismo: Zarządzanie Przedsiębiorstwem
• Rocznik: 2022
• Tom: Vol. 25, nr 1-2
• Strony: 7--14
• Opis fizyczny: Bibliogr. 22 poz., rys. kolor

Twórcy

autor

Majewski Wojciech

• Politechnika Poznańska, Wydział Inżynierii Mechanicznej, Piotrowo 3, 60-965 Poznań, Polska

autor

Dostatni Ewa

• Politechnika Poznańska, Wydział Inżynierii Mechanicznej, Piotrowo 3, 60-965 Poznań, Polska

autor

Diakun Jacek

• Politechnika Poznańska, Wydział Inżynierii Mechanicznej, Piotrowo 3, 60-965 Poznań, Polska

Bibliografia

• [1] Barbosa B.H.G., Xu N., Askari H., Khajepour A., Lateral force prediction using Gaussian process regression for intelligent tire systems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52, 8, 5332-5343, 2022.
• [2] Bęczkowska S., Korzeb J., Koziak S., Weyssenhoff A., Niejednorodność i wady materiałowe opon samochodów osobowych - zagadnienia wybrane, Prace Naukowe Politechniki Warszawskiej, Transport, z. 121, 9-20, 2018.
• [3] Chicu N., Prioteasa A.L., Deaconu A., Current trends and perspectives in tyre industry, Studia Universitatis “Vasile Goldis” Arad. Economics Series, 30, Special Issue 2, 36-56. 2020.
• [4] Chomka G., Chudy J., Kasperowicz M., Techniczne aspekty regeneracji opon samochodowych, Autobusy: Technika, Eksploatacja, Systemy Transportowe, 5110-115, 2012.
• [5] Funahashi T., Taki K., Koshimizu H., Kaneko A., Fast and robust visual inspection system for tire surface thin defect, 21st Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV), 1-6, 2015.
• [6] Gent A.N., Walter J.D., Pneumatic Tire, Mechanical Engineering Faculty Research, 2006.
• [7] Hadi H.A. et al., The implementation of Quality Function Deployment (QFD) in tire industry, ComTech Computer Mathematics and Engineering Applications, 8, 4, 223-228, 2017.
• [8] Jeong K.M., Kim K.W., Beom H.G., Park J.U., Finite element analysis of nonuniformity of tires with imperfections, Tire Science and Technology, TSTCA, 35, 3, 226-238, 2007.
• [9] Kosmela P., Olszewski A., Zedler Ł., Burger P., Formela K., Hejna A., Structural changes and their implications in foamed flexible polyurethane composites filled with rapeseed oil-treated ground tire rubber, J. Compos. Sci., 5, 90, 2021.
• [10] Li C., Research on tire dynamic balancing machine based on least square method, IEEE 6th International Conference on Intelligent Computing and Signal Processing (ICSP 2021), 2021.
• [11] Meng D., Pengfei S., Shuiting Z., Hongwu H., Jie Z., A study on the influence of tire speed and pressure on measurement parameters obtained from high-speed tire uniformity testing, MDPI, Vehicles, 2, 559-573, 2020.
• [12] Nan Xu, Hassan Askari, Yanjun Huang, Jianfeng Zhou, Amir Khajepour, Member, IEEE, Tire Force Estimation in Intelligent Tires Using Machine Learning, IEEE Transactions on Intelligent Transportation Systems, 23, 4, 2022.
• [13] Oertel C., Wei Y., Tyre rolling kinematics and prediction of tyre forces and moments: part I - Theory and method, Vehicle System Dynamics, 50, 11, 1673-1687, 2012.
• [14] Rodgers B., Waddell W., Science and technology of rubber (third edition), Academic Press, Chapter 14-Tire Engineering, 619-661, 2005.
• [15] Skarbek-Żabkin A., Kamińska E., Kierunki zagospodarowania zużytych opon samochodowych, Transport Samochodowy, 1, 2015.
• [16] Skrzyniarz M., Cykl życia odpadów gumowych na przykładzie zużytych opon samochodowych, Gospodarka Materiałowa i Logistyka, 9, 44-53, 2020.
• [17] Strano S., Terzo M., Tordela C., A supervised machine learning framework for smart tires, IEEE 6th International Forum on Research and Technology for Society and Industry (RTSI), 2021.
• [18] Sutthaweekul R., Buhari M., Sunny A.M., Tian G., Influence of lift-off on microwave open-ended waveguide time of flight based tire inspection, 2016 International Conference for Students on Applied Engineering (ICSAE), 275-279, 2016.
• [19] Tardiff J.L., Harper M., Haakenson D., Joandrea M., Knych M., Effect of sSBR composition, functionality on tire tread compound performance characteristics, Rubber World, 256, 6, 35-48, 2017.
• [20] Wei Y., Oertel C., Shen X., Tyre rolling kinematics and prediction of tyre forces and moments: part II - Simulation and experiment, Vehicle System Dynamics, 50, 11, 1689-1706, 2012.
• [21] Zasoby wewnętrzne firmy Brigdestone Poznań Sp. z o.o., 2022.
• [22] Zhu Q., Ai X., The Defect Detection Algorithm for Tire X-Ray Images Based on Deep Learning, IEEE 3rd International Conference on Image, Vision and Computing (ICIVC), 138-142, 2018.

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).