Application of Time-Series Analysis for Predicting Defects in Continuous Steel Casting Process

• Autorzy: Rodziewicz A. , Perzyk M.
• Języki publikacji: EN

Abstrakty

EN

The purpose of this paper was testing suitability of the time-series analysis for quality control of the continuous steel casting process in production conditions. The analysis was carried out on industrial data collected in one of Polish steel plants. The production data concerned defective fractions of billets obtained in the process. The procedure of the industrial data preparation is presented. The computations for the time-series analysis were carried out in two ways, both using the authors’ own software. The first one, applied to the real numbers type of the data has a wide range of capabilities, including not only prediction of the future values but also detection of important periodicity in data. In the second approach the data were assumed in a binary (categorical) form, i.e. the every heat(melt) was labeled as ‘Good’ or ‘Defective’. The naïve Bayesian classifier was used for predicting the successive values. The most interesting results of the analysis include good prediction accuracies obtained by both methodologies, the crucial influence of the last preceding point on the predicted result for the real data time-series analysis as well as obtaining an information about the type of misclassification for binary data. The possibility of prediction of the future values can be used by engineering or operational staff with an expert knowledge to decrease fraction of defective products by taking appropriate action when the forthcoming period is identified as critical.

Słowa kluczowe

EN

information technology; foundry industry; quality management; continuous steel casting; time series analysis; naïve Bayesian classifier

PL

technologia informatyczna; przemysł odlewniczy; zarządzanie jakością; odlewanie ciągłe stali; analiza szeregów czasowych; naiwny klasyfikator Bayesa

• Wydawca: Komisja Odlewnictwa Polskiej Akademii Nauk Oddział w Katowicach
• Czasopismo: Archives of Foundry Engineering
• Rocznik: 2016
• Tom: Vol. 16, iss. 4
• Strony: 125--130
• Opis fizyczny: Bibliogr. 7 poz., tab., wykr.

Twórcy

autor

Rodziewicz A.

• Institute of Manufacturing Technologies, Warsaw University of Technology, Narbutta 85, 02-524 Warszawa, Poland

autor

Perzyk M.

• Institute of Manufacturing Technologies, Warsaw University of Technology, Narbutta 85, 02-524 Warszawa, Poland

Bibliografia

• [1] Bisgaard, S. & Kulahci, M. (2008). Quality quandaries: Using a time series model for process adjustment and control. Quality Engineering. 20, 134-141. DOI: 10.1080/08982110701771042.
• [2] Lin, Z.C. & Chang, D.Y. (2009). A band-type network model for the time-series problem used for IC lead frame dam-bar shearing process. International Journal of Advanced Manufacturing Technology. 40(11-12), 1252-1266. DOI: 10.1007/s00170-008-1432-6.
• [3] Kapoor, S.G., Terry, R.W. (1983). Time series analysis of tensile strength in a die casting process. In Time Series Analysis: Theory and Practice 4, Proc. 8th International Time Series Meeting and 3rd American Conference, 1983 (pp. 221-228). Cincinnati, OH, USA: North-Holland, Amsterdam.
• [4] Camisani-Calzolari, F.R., Craig, I.K. & Pistorius, P.C. (2003). Quality prediction in continuous casting of stainless steel slabs. Journal of The South African Institute of Mining and Metallurgy. 103(10), 651-665.
• [5] Perzyk, M., Kochański, A., Biernacki, R., Kozłowski, J. & Soroczyński, A. (2011). Applications of data mining to diagnosis and control of manufacturing processes. In Kimito Funatsu and Kiyoshi Hasegawa(Eds.), Knowledge – Oriented Applications in Data Mining (pp. 147-166). Rijeka, Croatia: InTech. DOI: 10.5772/13282.
• [6] Perzyk, M., Krawiec, K. & Kozłowski, J. (2009). Application of time-series analysis in foundry production. Archives of Foundry Engineering. 9(3), 109-114.
• [7] Perzyk, M. & Rodziewicz, A. (2012). Application of Time-series Analysis in Control of Chemical Composition of Grey Cast Iron. Archives of Foundry Engineering. 12(4), 171-175. DOI: 10.2478/v10266-012-0127-5.

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.