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@article{145288,
        author = {Mohammad zuber khan and gourav purohit and indresh kumar jain},
        title = {Optimization Of Cutting Parameters For Surface Roughness In CNC Turning Using Taguchi And Regression Approach},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {4},
        number = {8},
        pages = {356-360},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=145288},
        abstract = {Prediction of surface roughness and dimensional inaccuracies is an essential prerequisite for any unmanned computer numeric controlled (CNC) machinery. This prediction technique is also important for optimization of machining process. In the present work, it is observed that, using Taguchi approach, the quality of surface finish can be predicted within a reasonable degree of accuracy by taking the triaxial cutting forces into account. Surface roughness and cutting forces are the critical factors which influence the quality of the machined parts. 
     In this research paper, an attempt has been made to optimize the cutting conditions to get predicted surface roughness in turning of Mild Steel. The experiment was designed using Taguchi full factorial approach and 27 experimental runs were conducted for various combinations of cutting parameters. The signal to noise ratio and analysis of variance (ANOVA) were employed to study the performance characteristics at different conditions. In order to analyze the response of the system, experiments were carried out at various spindle speeds, depth of cut and feed rate. The results obtained by this research will be useful for various industries and researchers working in this field.},
        keywords = {CNC; Surface roughness; Taguchi method;  ANOVA.},
        month = {},
        }