Optimization Technique For Surface Roughness Prediction in Turning Operation

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Gaurav Kumar Ojha
Gyanendra Kumar Yadav
Pankaj Yadav


Surface roughness has a great influence on the functional properties of the product. Finding the rules that how process factors and environment factors affect the values of surface roughness will help to set the process parameters of the future and then improve production quality and efficiency. Since surface roughness is impacted by different machining parameters and the inherent uncertainties in the machining process, how to predict the surface roughness becomes a challengeable problem for the researchers and engineers. In this paper an attempt is made to review the literature on optimizing machining parameters in turning processes. Various conventional techniques employed for machining optimization include geometric programming, geometric plus linear programming, goal programming, sequential unconstrained minimization technique, dynamic programming etc. The latest techniques for optimization include fuzzy logic, scatter search technique, genetic algorithm, Taguchi technique and response surface methodology.


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Ojha G, Yadav G, Yadav P. Optimization Technique For Surface Roughness Prediction in Turning Operation. sms [Internet]. 25Dec.2014 [cited 29Jan.2023];6(02):117-24. Available from: https://smsjournals.com/index.php/SAMRIDDHI/article/view/1136
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