Investigating the Design of Condition Monitoring Systems to Evaluate Surface Roughness under the Variability in Tool Wear and Fixturing Conditions

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Surface finish of machined parts in end milling operations is significantly influenced by process faults such as tool wear and tool holding (fixturing system). Therefore, monitoring these faults is considerably important to improve the quality of the product. In this paper, an investigation is presented to design the condition monitoring system to evaluate the surface roughness of the workpiece under effects of gradual tool wear and different types of the fixturing system. Automated Sensor and Signal Processing Selection (ASPS) approach is implemented and tested to determine the sensitivity of the sensory signals to estimate surface roughness under the variable conditions in comparison to surface roughness measurement device. The results indicate that the system is capable of detection the change and the trend in surface roughness. However, the sensitive features are found to be different based on the change in the fixturing system.

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467-470

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September 2013

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Oguz Colak, Cahit Kurbanoglu, and M. Cengiz Kayacan, in: Milling surface roughness prediction using evolutionary programming methods, Materials and Design, Vol. 28, Issue 2, (2007), pp.657-666.

DOI: 10.1016/j.matdes.2005.07.004

Google Scholar

[2] Vikas Upadhyay, P.K. Jain, N.K. Mehta, in: In-process prediction of surface roughness in turning of Ti–6Al–4V alloy using cutting parameters and vibration signals, Measurement, Vol. 46, Issue 1, (2013), pp.154-160.

DOI: 10.1016/j.measurement.2012.06.002

Google Scholar

[3] Preben Hansen, in: Solid contact, the advantages of dual and triple contact dual and triple contact tool holding systems for high speed machining, Vol. 53 , No. 7. (2001). E.

Google Scholar

[4] J. Abbas, A. Al-Habaibeh and D. SU, in: The Investigation of prediction surface roughness from machining forces in end milling processes, Key Eng. Materials. Vol 486, (2011), pp.91-94.

DOI: 10.4028/www.scientific.net/kem.486.91

Google Scholar

[5] A. Al-Habaibeh , Abd Al-Azmi, N. Radwan and Yang Song, in: The Application of Force and Acoustic Emission Sensors for Detecting Tool Damage in Turning Processes, Key Engineering Materials, Vols. 419-420, , (2010), pp.381-384.

DOI: 10.4028/www.scientific.net/kem.419-420.381

Google Scholar