Prediction of workpiece elastic deflections under cutting forces in turning

Benardos, PG; Mosialos, S; Vosniakos, GC

dc.contributor.author	Benardos, PG	en
dc.contributor.author	Mosialos, S	en
dc.contributor.author	Vosniakos, GC	en
dc.date.accessioned	2014-03-01T01:24:52Z
dc.date.available	2014-03-01T01:24:52Z
dc.date.issued	2006	en
dc.identifier.issn	0736-5845	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/17487
dc.subject	elastic deflection	en
dc.subject	cutting forces	en
dc.subject	CNC turning	en
dc.subject	elastic line	en
dc.subject	Artificial neural networks	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.subject.classification	Engineering, Manufacturing	en
dc.subject.classification	Robotics	en
dc.subject.other	UNIFIED-GENERALIZED MECHANICS	en
dc.subject.other	ERROR COMPENSATION	en
dc.subject.other	OPERATIONS	en
dc.subject.other	MODEL	en
dc.title	Prediction of workpiece elastic deflections under cutting forces in turning	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.rcim.2005.12.009	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.rcim.2005.12.009	en
heal.language	English	en
heal.publicationDate	2006	en
heal.abstract	One of the problems faced in turning processes is the elastic deformation of the workpiece due to the cutting forces resulting in the actual depth of cut being different than the desirable one. In this paper, a cutting mechanism is described suggesting that the above problem results in an over-dimensioned part. Consequently, the problem of determining the workpiece elastic deflection is addressed from two different points of view. The first approach is based on solving the analytical equations of the elastic line, in discretized segments of the workpiece, by considering a stored modal energy formulation due to the cutting forces. Given the mechanical properties of the workpiece material, the geometry of the final part and the cutting force values, this numerical method can predict the elastic deflection. The whole approach is implemented through a Microsoft Excel(C) workbook. The second approach involves the use of artificial neural networks (ANNs) in order to develop a model that can predict the dimensional deviation of the final part by correlating the cutting parameters and certain workpiece geometrical characteristics with the deviations of the depth of cut. These deviations are calculated with reference to final diameter values measured with precision micrometers or on a CMM. The verification of the numerical method and the development of the ANN model were based on data gathered from turning experiments conducted on a CNC lathe. The results support the proposed cutting mechanism. The numerical method qualitatively agrees with the experimental data while the ANN model is accurate and consistent in its predictions. (C) 2006 Elsevier Ltd. All rights reserved.	en
heal.publisher	PERGAMON-ELSEVIER SCIENCE LTD	en
heal.journalName	ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING	en
dc.identifier.doi	10.1016/j.rcim.2005.12.009	en
dc.identifier.isi	ISI:000240228600013	en
dc.identifier.volume	22	en
dc.identifier.issue	5-6	en
dc.identifier.spage	505	en
dc.identifier.epage	514	en