An empirical examination of the thickness profile formation of twin-roll-cast magnesium strips

• Autorzy: Kawalla C. , Höck M. , Ullmann M. , Ringle C. M.

Identyfikatory

DOI

10.1016/j.acme.2017.06.006

• Języki publikacji: EN

Abstrakty

EN

The recently developed technology of twin-roll-cast (TRC) magnesium strips permits an efficient production of magnesium sheets, primarily for the automotive industry. The focus of the paper is to develop a structural equation model explaining the variance of the thickness profile formation. Hence, the complex and partially unknown relationships between twin-roll casting process parameters and the thickness profile formation are analyzed using latent variables, e.g. the deformation resistance, length of contact arc, etc., which consist of several observed parameters. The fundamental process variables and their effect on the thickness profile formation during twin-roll casting are investigated and evaluated by partial least squares structural equation modeling (PLS-SEM) – a statistical method that fits networks of constructs to empirical data. The results of the predictive modeling technique allow an approximation of the existing interrelationships between thickness profiles, rolling force as well as processes in the roll gap which are typically difficult to measure directly using sensors. In this context, it was identified that the thickness profile variation is primarily caused by the forming force, which is mainly driven by the length of contact arc. Moreover, implications for the control of the thickness profile are derived.

Słowa kluczowe

EN

twin-roll casting process; quality assurance; thickness profile; structural equation modeling; partial least squares

PL

odlewanie; modelowanie równań strukturalnych; zapewnienie jakości

• Wydawca: Springer ; Wrocław University of Science and Technology
• Czasopismo: Archives of Civil and Mechanical Engineering
• Rocznik: 2018
• Tom: Vol. 18, no. 1
• Strony: 227--234
• Opis fizyczny: Bibliogr. 33 poz., rys., tab., wykr.

Twórcy

autor

Kawalla C.

• TU Bergakademie Freiberg, Institute of Industrial Management, Operations and Logistics, Freiberg, Germany

autor

Höck M.

• TU Bergakademie Freiberg, Institute of Industrial Management, Operations and Logistics, Freiberg, Germany

autor

Ullmann M.

• TU Bergakademie Freiberg, Institute of Metal Forming, Freiberg, Germany

autor

Ringle C. M.

• Hamburg University of Technology (TUHH), Institute of Human Resource Management and Organizations, Hamburg, Germany
• The University of Newcastle, Faculty of Business and Law, Newcastle, Australia

Bibliografia

• [1] A. Nam, U. Prüfert, M. Eiermann, R. Kawalla, Modelling the temperature evolution during hot reversing strip rolling of magnesium alloys, Trans Tech Publications – Materials Science Forum 854 (2016) 140–145.
• [2] A. Nam, U. Prüfert, R. Kawalla, Thermal modelling for production of hot strip of magnesium alloy, Journal of Machine Engineering 14 (2014) 29–38.
• [3] C. Kammer, D. Aluminium-Zentrale, Magnesium Taschenbuch, Aluminium-Verlag, Düsseldorf, 2000.
• [4] M.K. Kulekci, Magnesium and its alloys applications in automotive industry, The International Journal of Advanced Manufacturing Technology 39 (2008) 851–865.
• [5] H. Friedrich, S. Schumann, Research for a ‘‘new age of magnesium’’ in the automotive industry, Journal of Materials Processing Technology 117 (2001) 276–281.
• [6] R. Kawalla, M. Oswald, C. Schmidt, M. Ullmann, H.-P. Vogt, N. D. Cuong, New technology for the production of magnesium strips and sheets, Metalurgija 47 (2008) 195–198.
• [7] C. Kawalla, M. Hoeck, Quality assurance system for hot rolled TRC magnesium strips, Scientific Papers of Silesian University of Technology. Organization and Management Series 100 (2017) 171–179.
• [8] A. Miehe, U. Gross, Modelling of heat transfer and solidification processes in horizontal twin-roll casting of magnesium AZ31, IOP Publishing – IOP Conference Series 33 (2012) 1–8.
• [9] A. Miehe, Numerical Investigation of Horizontal Twin-Roll Casting of the Magnesium Alloy AZ31, 2014.
• [10] B. Frischknecht, G. Thun, Bandgießtechnologien – Stand der Technik und Trends, Aluminium 77 (2001) 746–751.
• [11] J. Strid, Twin roll casting, a technological over view, Proceedings of the 3rd International 3 (1992) 321–356.
• [12] U. Albrecht-Früh, Prozeßdatengestützte Modellbildung des Banddickenprofils beim Dünnbandgießen nach dem Zweirollenverfahren, Shaker Verlag, 1997.
• [13] H. Beyer-Steinhauer, Thermische Walzenbombierung beim Zwei-Rollen-Gießwalzverfahren, Verlag Stahleisen, 1993.
• [14] H. Hoffmann, R. Neugebauer, G. Spur (Eds.), Handbuch umformen, Carl Hanser Verlag GmbH & Co. KG, 2012.
• [15] S. Bernhard, Zur Regelung und Steuerung von Bandgiessanlagen nach dem Zwei-Rollen-Verfahren, VDI-Verlag, 1993.
• [16] M. Enning, Beitrag zur Dickenregelung beim Gießwalzen von Bändern, VDI-Verlag, 1990.
• [17] P.J. Ross (Ed.), Taguchi Techniques for Quality Engineering: Loss Function, Orthogonal Experiments, Parameter and Tolerance Design, 2nd edn., McGraw-Hill, New York, 1988.
• [18] W.-N. Pi, C. Low, Supplier evaluation and selection via Taguchi loss functions and an AHP, The International Journal of Advanced Manufacturing Technology 27 (2006) 625–630.
• [19] W. Tautz, EP 0 575 636 AI (10.06.92).
• [20] M. Degner, E. Neuschütz, Walzen von gleichmäßigem (keilfreiem) Warmbanddickenprofil: Europäische Kommission, Generaldirektion Forschung und Innovation, EUR, Luxembourg, 1998.
• [21] K.G. Jöreskog, Structural analysis of covariance and correlation matrices, Psychometrika 43 (1978) 443–477.
• [22] K.G. Jöreskog, The LISREL Approach to Causal Model-Building in the Social Sciences, Systems Under Indirect Observation. Part I, 1982, 81–100.
• [23] K.G. Jöreskog, A.S. Goldberger, Estimation of a model with multiple indicators and multiple causes of a single latent variable, Journal of the American Statistical Association 70 (1975) 631–639.
• [24] D.X. Peng, F. Lai, Using partial least squares in operations management research: a practical guideline and summary of past research, Journal of Operations Management 30 (2012) 467–480.
• [25] J.F. Hair, C.M. Ringle, M. Sarstedt, PLS-SEM: indeed a silver bullet, Journal of Marketing theory and Practice 19 (2011) 139– 152.
• [26] J.F. Hair, M. Sarstedt, C.M. Ringle, J.A. Mena, An assessment of the use of partial least squares structural equation modeling in marketing research, Journal of the Academy of Marketing Science 40 (2012) 414–433.
• [27] J.F. Hair, M. Sarstedt, T.M. Pieper, C.M. Ringle, The use of partial least squares structural equation modeling in strategic management research: a review of past practices and recommendations for future applications, Long Range Planning 45 (2012) 320–340.
• [28] C.M. Ringle, S. Wende, J.-M. Becker, SmartPLS 3, Boenningstedt: SmartPLS GmbH, 2015 http://www.smartpls. com.
• [29] J.F. Hair, G.T.M. Hult, C.M. Ringle, M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 2nd ed., Sage Publications, Thousand Oaks, 2017.
• [30] A. Diamantopoulos, P. Riefler, Formative Indikatoren: Einige Anmerkungen zu ihrer Art, Validität und Multikollinearität, Zeitschrift für Betriebswirtschaft 78 (2008) 1183–1196.
• [31] S. Geisser, A predictive approach to the random effect model, Biometrika (1974) 101–107.
• [32] M. Stone, Cross-validatory choice and assessment of statistical predictions, Journal of the royal statistical society: Series B (Methodological) (1974) 111–147.
• [33] M. Tenenhaus, V.E. Vinzi, Y.-M. Chatelin, C. Lauro, PLS path modeling, Computational Statistics & Data Analysis 48 (2005) 159–205.

Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018)