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Indicator analysis of the technological position of a manufacturing company

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A turbulent manufacturing market, especially in the metal industry, determines the quality of products and the level of production efficiency, which contributes to a company's market position and competitiveness. The aim of the study was to develop a model to define a manufacturing company’s current market position using KPIs in relation to a key product - gearbox casting. The company's position was defined in terms of the relationship occurring between technological capabilities and market position. An additional aim of the study was to identify critical determinants and, ultimately, to identify conditions for strengthening market position. As a test of the proposed model, the position of the analysed company (in terms of technological capabilities and market position) was defined as “Search for occasions”- box 9 within the 3x3 matrix. Technological determinants that weaken the company’s position (low level of maintenance capacity and long production cycle time) and determinants with a strong negative impact on market position (low level of human resource development) were identified. An element of novelty is the use of KPIs as variables determining the position of the company within the3x3 matrix, which is indicative of a specific technological position in the market. Further lines of research will concern the determination of appropriate KPIs in relation to the identified critical areas of the company. Subsequent steps will concern the implications of the model in relation to the company’s other key aluminium alloy castings.
Rocznik
Strony
162--167
Opis fizyczny
Bibliogr. 36 poz., rys., tab.
Twórcy
  • Rzeszow University of Technology, al. Powstańców Warszawy 12, 35-959 Rzeszow, Poland ;Tel.: + 178651390
  • Rzeszow University of Technology, al. Powstańców Warszawy 12, 35-959 Rzeszow, Poland
Bibliografia
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  • 2. Barbieri, N., Barbieri, GDV., Martins, BM., Barbieri, LDV., de Lima, KF., 2019. Analysis of automotive gearbox faults using vibration signal. Mechanical Systems And Signal Processing, 129, 148-163. DOI: 10.1016/j.ymssp.2019.04.028.
  • 3. Borkowski, S., Ulewicz, R., Selejdak J., Konstanciak, M., Klimecka‐Tatar, D., 2012. The use of 3x3 matrix to evaluation of ribbed wire manufacturing technology. in Proc. 21st Internatonal Conference on Metallurgy and Materials METAL 2012, 1722-1728.
  • 4. Borkowski, S., Ingaldi, M., Jagusiak-Kocik, M., 2014. The use of 3×3 matrix to evaluate a manufacturing technology of chosen metal company. Management Systems in Production Engineering, 3(15), 121-125.
  • 5. Daryani, SM., Khodaverdi, Y., Rasouli, E., Ehareghi, B., 2012. The importance of knowledge management technologies in performance improvement of organizations. Life Science Journal-Acta Zhengzhou University Overseas Edition, 9(9), 4695-4699.
  • 6. Deqiang, S., Zhijun, C., Hajduk-Stelmachowicz, M., Larik, AR.,Rafique, MZ. 2021., The role of the global value chain in improving trade and the sustainable competitive advantage: evidence from china’s manufacturing industry. Frontiers in Environmental Science, 9, 779295. DOI: 10.3389/fenvs.2021.779295
  • 7. Di Luozzo, S., Keegan, R., Liolli, R., Schiraldi, MM., 2022. Key activity indicators: critical review and proposal of implementation criteria, International Journal Of Productivity And Performance Management, DOI: 10.1108/IJPPM-01-2022-0023.
  • 8. Gawlik, R., 2016. Methodological aspects of qualitative-quantitative analysis of decision-making processes. Management And Production Engineering Review, 7(2), 3-11. DOI: 10.1515/mper-2016-0011.
  • 9. Hren, JA., Michna, S., Michnova, L., 2019. Dependence of mechanical properties on porosity of alsi7mg0.3 alloy during gravity casting. 18th International Scientific Conference Engineering For Rural Development, Engineering for Rural Development, 1001-1006. DOI: 10.22616/ERDev2019.18.N076.
  • 10. Hristov, I., Chirico, A., The role of sustainability key performance indicators (KPIs) in implementing sustainable strategies, Sustainability, 11(20), DOI: 10.3390/su11205742
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  • 18. Ligarski, MJ., Rozalowski, B., Kalinowski, K., 2021. A study of the human factor in industry 4.0 based on the automotive industry. Energies, 14(20), 6833. DOI: 10.3390/en14206833.
  • 19. Lyp-Wrońska, K., Wolniak, R., Sulkowski, M., 2018. determinant of quality in metalworking enterprises. 27th International Conference On Metallurgy And Materials (Metal 2018), 2029-2035.
  • 20. Makarova, I., Mukhametdinov, E., Gabsalikhova, L., Shepelev, V., Galiev, S., Buyvol, P., Drakaki, M., 2021. Ensuring reliability of the gearbox during operation stage. Proceedings Of The 7th International Conference On Vehicle Technology And Intelligent Transport Systems (Vehits), 768-774. DOI: 10.5220/0010530707680774.
  • 21. Maszke, A., Dwornicka, R., Ulewicz, R., 2018. Problems in the implementation of the lean concept at a steel works - Case study. MATEC Web of Conferences, 183.
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  • 29. PN-EN 1706:2011, Aluminum and aluminum alloys Castings. Chemical composition and mechanical properties, 2011, Warszawa: PKN.
  • 30. PN-EN 15341:2007, Maintenance – Maintenance Key Performance Indicators. 2007, Warszawa, PKN.
  • 31. Siegfanz, S., Gietler, A., Michels, W., Krupp, U., 2013. Influence of the microstructure on the fatigue damage behaviour of the aluminium cast alloy AlSi7Mg0.3, Materials Science and Engineering A-Structural Materials Properties Microstructure And Processing, 565, 21-26. DOI: 10.1016/j.msea.2012.12.047.
  • 32. Ulewicz, R., Czerwińska, K., Pacana, A., 2022. A Rank Model of Casting Non-Conformity Detection Methods in the Context of Industry 4.0. Materials 2023, 16, 723, DOI: 10.3390/ma16020723.
  • 33. Ulewicz, R., Mazur, M., 2019. Economic aspects of robotization of production processes by example of a car semi-trailers manufacturer. Manufacturing Technology, 19(6), 1054–1059
  • 34. Werner, MJE., Yamada, APL., Domingos, EGN., Leite, LR, Pereira, CR., 2021. Exploring organizational resilience through key performance indicators. Journal Of Industrial And Production Engineering, 38(1), 51-65, DOI: 10.1080/21681015.2020.1839582
  • 35. Wolniak, R., Szeptuch, A., Ziecina, G. 2017. Analysis of behavior of management in an international metallurgical company. using Cameron and Quinn typology, E-mentor, 2, 60-69.
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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-8034ef3f-ab63-4075-a6c3-1afea251c205
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