Articles written in Sadhana
Volume 38 Issue 3 June 2013 pp 491-511
This paper presents an experimental and statistical study on noise level generated during of rock sawing by circular diamond sawblades. Inﬂuence of the operating variables and rock properties on the noise level are investigated and analysed. Statistical analyses are then employed and models are built for the prediction of noise levels depending on the operating variables and the rock properties. The derived models are validated through some statistical tests. It is found that increasing of peripheral speed, traverse speed and cutting depth result in an increase in noise levels. On the other hand, a decreasing trend for noise levels is initially observed with the increasing of ﬂow rate of cooling ﬂuid. It is also determined that there are moderate correlations between uniaxial compressive strength, density and noise levels. Furthermore, the modelling results reveal that the predictive models have high potentials as guidance for practical applications.
Volume 39 Issue 5 October 2014 pp 1055-1070
In this paper, an optimization study was carried out for the cutting force (Fc) acting on circular diamond sawblades in rock sawing. The peripheral speed, traverse speed, cut depth and flow rate of cooling fluid were considered as operating variables and optimized by using Taguchi approach for the Fc. L16(44) orthogonal array was chosen for the experimental trials based on the operating variables and their levels. The signal-to-noise (S/N) ratios and the analysis of variance (ANOVA) were employed to determine optimum cutting conditions and significant operating variables, respectively. The Fc was also modelled based on the operating variables using regression analysis. The developed model was then verified using various statistical approaches. The results revealed that the operating variables of circular diamond sawblades can be precisely optimized by Taguchi approach for the Fc in rock sawing. The cut depth and peripheral speed were statistically determined as the significant operating variables affecting Fc. Furthermore, the modelling results showed that the proposed model can be effectively used for the prediction of Fc in practical applications.