Tool vibration effect on surface roughness of polymethylmethacrylate in diamond turning

Author(s):  
Kuldeep A Mahajan ◽  
Raju S. Pawade ◽  
Vinod Mishra
2012 ◽  
Vol 2 (6) ◽  
pp. 268-270 ◽  
Author(s):  
Harinderpal Singh Harinderpal Singh ◽  
◽  
Rahul O vaishya ◽  
Karanvir Sing ◽  
Vinod Mishra ◽  
...  

Author(s):  
Menderes Kam ◽  
Mustafa Demirtaş

This study analyzed the tool vibration (Vib) and surface roughness (Ra) during turning of AISI 4340 (34CrNiMo6) tempered steel samples using Taguchi Method. In this context, Taguchi design L18 (21 × 32) was used to analyze the experimental results. The vibration amplitude values from cutting tools were recorded for different machining parameters, control factors; two different sample hardness (46 and 53 HRc), three different cutting speeds (180, 220, 260 m.min−1), and feed rates (0.08, 0.14, 0.20 mm.rev−1) were selected. The machining parameters giving optimum Vib and Ra values were determined. Regression analysis is applied to predict values of Vib and Ra. Analysis of variance was used to determine the effects of machining parameters on the Vib and Ra values. The most important machining parameters were found to be the feed rate, sample hardness, and cutting speed for Vib and Ra, respectively. The lowest Vib and Ra values were obtained in 46 HRc sample as 0.0022 gRMS and 0.255 µm, respectively. The surface quality can be improved by reducing the sources of vibration by using appropriate machining parameters. As a result, there is a significant relationship between Ra and Vib. The lower Ra values were found during turning process of tempered steel samples according to the literature studies. It is suggested that the process can be preferred as an alternative process to grinding process due to lower cost and machining time. In application of the turning of experiment samples by ceramic cutting tool, a substantial technological and economical benefit has been observed.


2015 ◽  
Vol 82 ◽  
pp. 216-222 ◽  
Author(s):  
C.L. He ◽  
W.J. Zong ◽  
Z.M. Cao ◽  
T. Sun

2019 ◽  
Vol 287 ◽  
pp. 30-34
Author(s):  
Zwelinzima Mkoko ◽  
Khaled Abou-El-Hossein

In the globally competitive environment, surface roughness and finer tolerances are becoming stringent and certainly most critical for optical components. The aim of this study is to determine the effects of diamond turning process parameters on surface finish when diamond turning RSA 443 alloy having high silicon content. This alloy is a new grade of aluminum that has a potential to be used for production of various optical components. The experiments were conducted based on the Box-Behnken design with three diamond-turning parameters varied at three levels. A mathematical regression model was developed for predicting surface roughness. Further, the analysis of variance was used to analyze the influence of cutting parameters and their interaction in machining. The developed prediction model reveals that cutting speed and feed rate are the most dominant diamond turning factors influencing surface roughness.


2019 ◽  
pp. 089270571985060
Author(s):  
Muhammad Mukhtar Liman ◽  
Khaled Abou-El-Hossein ◽  
Lukman Niyi Abdulkadir

Due to increasing demand for high accuracy and high-quality surface finish in optical industry, contact lens manufacturing requires reliable models for predicting surface roughness (Ra) which plays a very important role in the optical manufacturing industry. In this study, a Nanoform 250 ultra-grind turning machine was used for machining, while cutting speed, feed rate, and the depth of cut (with values selected to cover a wide range based on the literature) were considered as the machining parameters for a diamond turned rigid polymethylmethacrylate (PMMA) contact lens polymer. Turning experiments were designed and conducted according to Box–Behnken design which is a response surface methodology technique. Fuzzy logic-based artificial intelligence method was employed to develop an electrostatic charge (ESC), Ra, and material removal rate (MRR) prediction models. The accuracy and predictive ability of the fuzzy logic model was then judged by considering an average percentage error between experimental values and fuzzy logic predictions. Further, a comparative evaluation of experiments and fuzzy logic approach showed that the average errors of ESC, Ra, and MRR using fuzzy logic system were in tandem with experimental results. Hence, the developed fuzzy logic rules can be effectively utilized to predict the ESC, Ra, and MRR of a rigid PMMA contact lens polymers in automated optical manufacturing environments for high accuracy and computational cost.


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