The use of selected SPC tools in the analysis of the quality of pig iron
The main goal of the paper was to determine the importance of using statistical quality assessment tools used in SPC to optimize quality from the point of view of obtaining stable results that meet the requirements set by customers or technical documentation. The analysis of quality parameters of blast furnace pig iron produced by a selected production plant was carried out, in which selected SPC tools were used. The analysis used data from the output of the production process and concerning the quality of the finished product, i.e. metallurgical pig iron. The following parameters: content of Si, Mn, P, S, C and the temperature of the finished product were analysed. The analysis included results from tests from 36 consecutive calendar months. Control charts of average values and quality capability indices were used to evaluate selected quality parameters.
References
Bibliografia/References
Alaeddini, A., & Dogan, I. (2011). Using Bayesian networks for root cause analysis in statistical process control. Expert Systems with Applications, 38(9), 11230–11243. https://doi.org/10.1016/j.eswa.2011.02.171
Almeida, T. S., dos Santos Mendes, A., Rocha Rizol, P. M. S., & Machado, M. A. G. (2023). Performance analysis of interval type-2 fuzzy X and R control charts. Applied Sciences, 13(20), 11594. https://doi.org/10.3390/app132011594
Breen, S. L., Moseley, D. J., Zhang, B., & Sharpe, M. B. (2008). Statistical process control for IMRT dosimetric verification. Medical Physics, 35(10). https://doi.org/10.1118/1.2975144
Chaudhary, A. M., Sanaullah, A., Hanif, M., Almazah, M. M. A., Albasheir, N. A., & Al-Duais, F. S. (2023). Efficient monitoring of a parameter of non-normal process using a robust efficient control chart: A comparative study. Mathematics, 11, 4157. https://doi.org/10.3390/math11194157
Ebel, M. (2000). SPC – Statistische Prozessregelung. GRIN Verlag.
Gejdoš, P. (2016). Continuous quality improvement by statistical process control. Procedia Economics and Finance, 34, 565–572. https://doi.org/10.1016/S2212-5671(15)01669-X
Godina, R., Matias, J., & Azevedo, S. (2016). Quality improvement with statistical process control in the automotive industry. International Journal of Industrial Engineering and Management (IJIEM), 7(1), 1–8. https://doi.org/10.24867/IJIEM-2016-1-101
Hamrol, A. (2023). Zarządzanie i inżynieria jakości ze spojrzeniem na rzeczywistość 4.0. Wydawnictwo Naukowe PWN.
Huang, W. H. (2022). The performance of S control charts for the lognormal distribution with estimated parameters. Sustainability, 14, 16582. https://doi.org/10.3390/su142416582
Kaźmierczak, M. (2024). Monitorowanie procesów i jakości w usługach. Ekonomika i Organizacja Przedsiębiorstwa, 6, 85–91.
MacCarthy B. L., & Wasusri, T. (2002). A review of non-standard applications of statistical process control (SPC) charts. International Journal of Quality & Reliability Management, 19(3), 295–320. https://doi.org/10.1108/02656710210415695
Madanhiren, I., & Mbohwa, C. (2016). Application of statistical process control (SPC) in manufacturing industry in a developing country. Procedia CIRP, 40, 580–583. https://doi.org/10.1016/j.procir.2016.01.137
Motorcu, A. R, & Güllü, A. (2006). Statistical process control in machining. A case study for machine tool capability and process capability. Materials and Design, 27, 364–372. https://doi.org/10.1016/j.matdes.2004.11.003
PN-EN 10001:1996 Surówka żelaza – określenie i klasyfikacja.
Rogala, P. (2012). Tożsamość zarządzania jakością – wybrane zagadnienia. Zarządzanie i Finanse, 10(3), 61–69. http://jmf.wzr.pl/pim/2012_3_1_5.pdf
Sałaciński, T., Chrzanowski, J., & Chmielewski, T. (2023). Statistical process control using control charts with variable parameters. Processes, 11, 2744. https://doi.org/10.3390/pr11092744
Schulze, A. (2014). Statistische Prozesslenkung (SPC). Carl Hanser Fachbuchverlag.
Scordaki, A., & Psarakis, S. (2005). Statistical process control in service industry an application with real data in a commercial company. In: Proceedings of the 7th Hellenic European Conference on Computer Mathematics and Its Applications. Athens, Greece.
Zasadzień, M. (2017). Statistical process control in the maintenance. Systemy wspomagania w inżynierii produkcji, 6(4), 159–165.