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The Product and Process Quality Level Analysis in the Automotive Elements Production Management

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The article presents the results of research carried out in the chosen company producing components for automotive companies. The main objective of the research was to analyze the quality level in the production of assembly parts for the automotive industry with regard to customer requirements, carried out by using the product FMEA and process FMEA methods. The research were conducted based on results of the company quality control and calculations have been conducted with applying Excel program. Results of data analysis presented in the paper indicate the main areas connected with occurrence of nonconformities that affected the final quality of the product. Analysis of research results using the FMEA method allowed to find not only the source of quality problems in the production process. It also allowed us to indicate recommendations for system improvements. The recommended actions not only allow for streamlining the production process, but also affect the quality level of the product at every stage of its production, which can be successfully found in other companies in the automotive industry.
Słowa kluczowe
Wydawca
Rocznik
Tom
Strony
514--524
Opis fizyczny
Bibliogr. 29 poz., rys., tab.
Twórcy
  • Czestochowa University of Technology Faculty of Management Department of Production Engineering and Safety ul. Dabrowskiego 69, 42-201 Czestochowa, Poland
autor
  • Chongqing Key Laboratory for advanced Materials and Technologies of Clean Energies School of Materials and Energy Southwest University Chongqing, 400715, P.R. China
Bibliografia
  • [1] S. Takata, F. Kirnura, F.J.A.M. Van Houten, E. Westkamper, M. Shpitalni, D. Ceglarek, J. Lee Maintenance, “Changing Role in Life Cycle Management. CIRP Annals – Manufacturing Technology, vol. 53, issue 2, 2004, pp. 643-655.
  • [2] M. Colledani, T. Tolio, A. Fischer, B. Iung, G. Lanza, R. Schmitt, J. Váncza, “Design and management of manufacturing systems for production quality”, CIRP Annals, vol. 63, issue 2, 2014, pp. 773-796.
  • [3] R. Chougule, V.R. Khare, K.A. Pattada, “Fuzzy Logic Based Approach for Modeling Quality and Reliability Related Customer Satisfaction in the Automotive Domain”. Expert Syst. Appl. 2013, vol. 40, pp. 800-810. https://doi.org/10.1016/j.eswa.2012.08.032.
  • [4] W. Ostasiewicz, “Ocena i analiza jakości życia”, Wydawnictwo Akademii Ekonomicznej im. Oskara Langego we Wrocławiu, Wrocław, 2004, pp. 118-120.
  • [5] A. Szczyrba, M. Ingaldi, “Implementation of the FMEA Method as a Support for the HACCP System in the Polish Food Industry”, Management Systems in Production Engineering, vol. 32, no 3, 2024, pp. 357-371, https://doi.org/10.2478/mspe-2024-0034.
  • [6] A. Hamrol, “Zarządzanie jakością z przykładami”, PWN, Warszawa, 2005, pp. 19.
  • [7] A. Iwasiewicz, “Zarządzanie jakością”, PWN, Warszawa-Kraków, 1999, pp. 22.
  • [8] F. Mroczko, “Zarządzanie jakością”, Prace Naukowe Wał-brzyskiej Wyższej Szkoły Zarządzania i Przedsiębiorczości, Seria: Zarządzanie, 2012, pp. 17-25.
  • [9] J. Brdulak, J. Lewicki, “Zapewnienie jakości – przegląd współczesnych modeli oraz rekomendacje dla podmiotów zewnętrznego zapewnienia jakości (PZZJ)”, Instytut Badań Edukacyjnych, Warszawa, 2022, pp. 6-15.
  • [10] K. Łyp-Wrońska, J. Buliński, “System jakości w praktyce. Quality system in practice”, Praktyka zarządzania jakością w XXI wieku. The practice of quality management in the XXI century, ed. T. Sikora and M. Giemza, Uniwersytet Ekonomiczny w Krakowie, Kraków 2012, pp.590-591.
  • [11] A. Kowalczyk, A. Maleszka, “Metody i techniki zarządzania jakością w branży motoryzacyjnej”, Akademia Ekonomiczna, Kraków 2010, pp. 524-535.
  • [12] J. Cieśla, R. Ulewicz, “The Future of Automotive Quality Control: How Cloud-Based Reporting is Changing the Game”, Management Systems in Production Engineering, vol. 32, no 1, pp. 72-79, https://doi.org/10.2478/mspe-2024-0008.
  • [13] R. Sanchez-Marquez, J.M. Albarracín Guillem, E. Vicens-Salort, J. Jabaloyes Vivas, “Diagnosis of quality management systems using data analytics – A case study in the manufacturing sector”, Computers in Industry, vol. 115, 2020, https://doi.org/10.1016/j.compind.2019.103183.
  • [14] S. Sahoo, “Assessing lean implementation and benefits within Indian automotive component manufacturing SMEs”, Benchmarking: An International Journal, vol. 27 No. 3, 2020, pp. 1042-1084, Emerald Publishing Limited 1463-5771, https://doi.org/10.1108/BIJ-07-2019-0299.
  • [15] https://asq.org/quality-resources/quality-glossary/f [access: 28.09.2024].
  • [16] C.L. Chang, C.C. Wei, Y.H. Lee, “Failure mode and effects analysis using fuzzy method and grey theory”, Kybernetes, vol. 28, 1999, pp. 1072-1080.
  • [17] M. Ben-Daya, A. Raouf, “A revised failure mode and effects analysis model”, International Journal of Quality and Reliability Management, vol. 13, no. 1, 1996, pp. 43-47.
  • [18] A.C. Kutlu, M. Ekmekcioglu, “Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP”, Expert Systems with Applications, vol. 39, 2012, pp. 61-67.
  • [19] A.P. Subriadi, N.F. Najwa, “The Consistency Analysis of Failure Mode and Effect Analysis (FMEA) in Information Technology Risk Assessment”, Heliyon, 2020, vol. 6, issue 1. https://doi.org/10.1016/j.heliyon.2020.e03161.
  • [20] S. Rastayesh, S. Bahrebar, F. Blaabjerg, D. Zhou, H. Wang, J.A. Dalsgaard Sørensen, “System Engineering Approach Using FMEA and Bayesian Network for Risk Analysis – A Case Study”, Sustainability, 2020, vol. 12, issue 77, https://doi.org/10.3390/su12010077
  • [21] A. Kania, K. Cesarz-Andraczke, J. Odrobiński, J. “Application of FMEA method for an analysis of selected production proces”, Journal of Achievements in Materials and Manufacturing Engineering, vol. 91, issue 1, 2018, pp. 34-40. https://doi.org/10.5604/01.3001.0012.9655
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  • [23] R. Wolniak, “Problems of use of FMEA method in industrial enterprise”, Production Engineering Archives, vol. 23, 2019, pp. 12-17. https://doi.org/10.30657/pea.2019.23.02.
  • [24] H.C. Liu, J. X. You, Q.L. Lin, H. Li, “Risk assessment in system FMEA combining fuzzy weighted average with fuzzy decision-making trial and evaluation laboratory”, International Journal of Computer Integrated Manufacturing, vol. 28, no. 7, 2014, pp. 701-714. https://doi.org/10.1080/0951192X.2014.900865.
  • [25] https://www.aiag.org/about/news/2019/06/03/aiag-andvda-release-new-automotive-fmea-handbook [access 28.09.2024].
  • [26] R. Moen, C. Norman, “Evolution of the PDCA Cycle”, “The History of the PDCA Cycle.” In Proceedings of the 7th ANQ Congress, Tokyo, 2009, Asian Network for Quality https://www.anforq.or,g/activities/congresses/index.html.
  • [27] Godina, Radu, Beatriz Gomes Rolis Silva, and Pedro Espadinha-Cruz. 2021. “A DMAIC Integrated Fuzzy FMEA Model: A Case Study in the Automotive Industry”, Applied Sciences, vol. 11, no. 8, pp. 3726. https://doi.org/10.3390/app11083726.
  • [28] F. Crawley, F., “Failure modes and effects analysis (FMEA) and failure modes, effects and criticality analysis (FMECA).” A guide to hazard identification methods, 2020, pp. 103-109.
  • [29] L. Petrescu, E. Cazacu, M.C. Petrescu, “Failure mode and effect analysis in automotive industry: a case study”, The Scientific Bulletin of Electrical Engineering Faculty, vol. 19, issue 2, pp. 10-15. https://doi.org/10.1515/SBEEF-2019-0014.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki i promocja sportu (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-bd6236e0-0805-4f65-a984-a1f8e4283d47
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