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Sensors 2014, 14(4), 6393-6408; doi:10.3390/s140406393

Surface Roughness Model Based on Force Sensors for the Prediction of the Tool Wear

Department of Manufacturing Engineering, Industrial Engineering School, National University of Distance Education (UNED), C/Juan del Rosal, 12, E28040-Madrid, Spain
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Received: 7 February 2014 / Revised: 12 March 2014 / Accepted: 28 March 2014 / Published: 4 April 2014
(This article belongs to the Section Physical Sensors)
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Abstract

In this study, a methodology has been developed with the objective of evaluating the surface roughness obtained during turning processes by measuring the signals detected by a force sensor under the same cutting conditions. In this way, the surface quality achieved along the process is correlated to several parameters of the cutting forces (thrust forces, feed forces and cutting forces), so the effect that the tool wear causes on the surface roughness is evaluated. In a first step, the best cutting conditions (cutting parameters and radius of tool) for a certain quality surface requirement were found for pieces of UNS A97075. Next, with this selection a model of surface roughness based on the cutting forces was developed for different states of wear that simulate the behaviour of the tool throughout its life. The validation of this model reveals that it was effective for approximately 70% of the surface roughness values obtained.
Keywords: dry turning; aluminum alloys; force sensor; surface roughness models; tool wear; design of experiments; ANOVA; regression dry turning; aluminum alloys; force sensor; surface roughness models; tool wear; design of experiments; ANOVA; regression
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

de Agustina, B.; Rubio, E.M.; Sebastián, M. Surface Roughness Model Based on Force Sensors for the Prediction of the Tool Wear. Sensors 2014, 14, 6393-6408.

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