Abstract
The paper presents classifier models in intelligent computer aided process planning (CAPP) systems. The models of simple classifiers and models of multiple classifiers are compared in order to obtain optimal classification. The models are tested on real data from an enterprise. Based on the classification models, the intelligent support system allows to create scenarios for selection of tools to manufacturing operations. Therefore the embedded models improve this selection. We present decision trees as models for classifcation in intelligent CAPP systems. The research was done for selected manufacturing operations: turning, milling and grinding. Models for milling operation were presented in detail.
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Rojek, I. (2009). Classifier Models in Intelligent CAPP Systems. In: Cyran, K.A., Kozielski, S., Peters, J.F., Stańczyk, U., Wakulicz-Deja, A. (eds) Man-Machine Interactions. Advances in Intelligent and Soft Computing, vol 59. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00563-3_32
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DOI: https://doi.org/10.1007/978-3-642-00563-3_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00562-6
Online ISBN: 978-3-642-00563-3
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