Experimental and Numerical Studies of Wire Vibrations in Bonded Abrasive Wire Saw Processing
Abstract
Bonded Abrasive Wire (BAW) saw slicing is a popular method for silicon carbide wafer production; however, the wires are highly susceptible to vibrations. In this paper, a vibration model of the wire saw is presented, and a numerical analysis of this model, which is confirmed by experiments, is developed. The experiments show that the model can predict vibration characteristics of wire saw with no processing or processing and the biggest error of model in frequency domain is 10.6%. Moreover, the wire tension is an important factor for wire saw vibration. The experiments show that a 50% increase in tension may make a 43.2% increase in vibration frequency, and the relationship is not linear depended on tension control device.
Recommended Citation
A. Tang et al., "Experimental and Numerical Studies of Wire Vibrations in Bonded Abrasive Wire Saw Processing," Proceedings of the 2016 International Symposium on Flexible Automation (2016, Cleveland, OH), pp. 133 - 140, Institute of Electrical and Electronics Engineers (IEEE), Aug 2016.
The definitive version is available at https://doi.org/10.1109/ISFA.2016.7790149
Meeting Name
2016 International Symposium on Flexible Automation, ISFA2016 (2016: Aug. 1-3, Cleveland, OH)
Department(s)
Mechanical and Aerospace Engineering
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
Abrasives; Frequency domain analysis; Sawing; Silicon carbide; Silicon wafers; Wire; Experimental and numerical studies; Frequency domains; Silicon carbide wafers; Tension controls; Vibration characteristics; Vibration frequency; Vibration model; Wire vibrations; Vibration analysis
International Standard Book Number (ISBN)
978-1-5090-3467-3
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2016 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Aug 2016
Comments
The authors wish to acknowledge the financial support for this work from the National Natural Science Foundation of China (51105303, 51175420, and 51575442), the Shaanxi Province Education Department (00S1409), and China Postdoctoral Science Foundation funded project (20110491673), and the Intelligent Systems Center at the Missouri University of Science and Technology.