Abstract
A software concept based on data mining and knowledge discovery for a multi-spindle drilling gear configuration and optimisation applied to a machine used in furniture production process is proposed. The objective is to find the minimum number of supports and the optimised configuration of the multi-spindle drilling gears. Intelligent analysis of input data and an automated system covering the human design procedure are applied to configure multi-drilling gears. The input data presented as digitalised customer engineering drawings and furthermore technology data describing the basic constraints of the machine construction are presented. Moreover the transfer of acquired manual design experience from a human expert to a software strategy to solve the multi-criteria optimisation problem is shown.
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References
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© 2001 Springer-Verlag Wien
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Klene, G., Grauel, A., Convey, H.J., Hartley, A.J. (2001). Data Mining and Automation of Experts Decision Process Applied to Machine Design for Furniture Production. In: Kůrková, V., Neruda, R., Kárný, M., Steele, N.C. (eds) Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6230-9_113
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DOI: https://doi.org/10.1007/978-3-7091-6230-9_113
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-83651-4
Online ISBN: 978-3-7091-6230-9
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