OPTIMAL MQL AND CUTTING CONDITIONS DETERMINATION FOR DESIRED SURFACE ROUGHNESS IN TURNING OF BRASS USING GENETIC ALGORITHMS |
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| Authors: | V N Gaitonde S R Karnik J Paulo Davim |
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| Affiliation: | 1. Department of Industrial and Production Engineering , B. V. B. College of Engineering and Technology , Hubli , Karnataka , India gaitondevn@yahoo.co.in;3. Department of Electrical and Electronics Engineering , B. V. B. College of Engineering and Technology , Hubli , Karnataka , India;4. Department of Mechanical Engineering , University of Aveiro, Campus Santiago , Aveiro , Portugal |
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| Abstract: | The evolving concept of minimum quantity of lubrication (MQL) in machining is considered as one of the solutions to reduce the amount of lubricant to address the environmental, economical and ecological issues. This paper investigates the influence of cutting speed, feed rate and different amount of MQL on machining performance during turning of brass using K10 cemented carbide tool. The experiments have been planned as per Taguchi's orthogonal array and the second order surface roughness model in terms of machining parameters was developed using response surface methodology (RSM). The parametric analysis has been carried out to analyze the interaction effects of process parameters on surface roughness. The optimization is then carried out with genetic algorithms (GA) using surface roughness model for the selection of optimal MQL and cutting conditions. The GA program gives the minimum values of surface roughness and the corresponding optimal machining parameters. |
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| Keywords: | brass genetic algorithms Minimum Quantity of Lubricant (MQL) Response Surface Methodology (RSM) surface roughness turning |
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