Abstract
Rough machining removes the excess part material and dominates the machining time of a sculptured part. Maximization of the material removal rate using optimized cutting parameters for rough machining can considerably improve productivity. This work focuses on the identification, improvement and testing of a machining process model that is generally applicable to various cutting geometry, as well as model parameters that cover a broad range of cutting conditions. A method for acquiring machining parameters of various 2 ½ D milling operations for a generic cutting force model is proposed. The improved cutting force model requires few cutting tests, provides fast and accurate predictions, and supports future upgrading. Testing has shown a good agreement between predicted and measured cutting forces. A considerable saving of machining time can be achieved.
The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-0-387-35392-0_40
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© 1999 IFIP International Federation for Information Processing
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Pop, S.I., Vickers, G.W., Dong, Z. (1999). Machining Process Modeling for Intelligent Rough Machining of Sculptured Parts. In: Olling, G.J., Choi, B.K., Jerard, R.B. (eds) Machining Impossible Shapes. IFIP — The International Federation for Information Processing, vol 18. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35392-0_12
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DOI: https://doi.org/10.1007/978-0-387-35392-0_12
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4757-5690-6
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