Abstract
The calibration of a tablet press machine requires comprehensive experiments and is therefore expensive and time-consuming. In order to optimize the process parameters of a tablet press machine on the basis of measured data this paper presents a new approach that works with the application of local model networks. Goal of the model-based optimization was the improvement of the quality of produced tablets, i.e. the reduction of capping occurence and the variation of the tablet mass as well as the variation of the crushing strength. Modeling and optimization of the tablet process parameters show that it is possible to find process settings for the tabletting of non-preprocessed powder such that a sufficient quality of the tablets can be achieved.
This work was supported by the German Research Foundation (DFG), grant NE 656/3–1.
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Hartmann, B., Nelles, O., Belič, A., Zupančič–Božič, D. (2009). Local Model Networks for the Optimization of a Tablet Production Process. In: Deng, H., Wang, L., Wang, F.L., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2009. Lecture Notes in Computer Science(), vol 5855. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05253-8_27
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DOI: https://doi.org/10.1007/978-3-642-05253-8_27
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