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Selection of Optimum Machining Parameters for Surface Grinding Operations Using Simulated Annealing (SA) Algorithm


Affiliations
1 School of Mechanical Engineering, Shanmuga Arts Science Technology and Research Academy, Thanjavur-613402, India
2 Department of Production Engineering, National Institute of Technology, Trichy, India
3 Department of Mechanical Engineering, J.J College of Engineering and Technology, Trichy, India
     

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A Simulated Annealing (SA) based optimization procedure has been developed to optimize grinding conditions viz. wheel speed, workpiece speed, depth of dressing and lead of dressing, using multi-objective function model with a weighted approach for surface grinding process. The procedure evaluates the production cost, production rate and surface finish for optimum grinding conditions, subjected to thermal damage, wheel-wear parameter, machine-tool stiffness and surface finish or production rate constraints. A computer program written in Visual C++ has been developed for optimization computations. The program prompts the user to input or modify all the constants related to the grinding operations. All the constants used here are default values, unless over-written by the user. User can also alter the specific Input values to perform sensitivity analysis of the relative contributions of grinding parameters to the weighted objective function. Simulated Annealing (SA) optimization is illustrated with an example and the optimum results are compared with Quadratic programming and Genetic Algorithm techniques.
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  • Selection of Optimum Machining Parameters for Surface Grinding Operations Using Simulated Annealing (SA) Algorithm

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Authors

K. Babu
School of Mechanical Engineering, Shanmuga Arts Science Technology and Research Academy, Thanjavur-613402, India
N. Baskar
School of Mechanical Engineering, Shanmuga Arts Science Technology and Research Academy, Thanjavur-613402, India
P. Asokan
Department of Production Engineering, National Institute of Technology, Trichy, India
R. Saravanan
Department of Mechanical Engineering, J.J College of Engineering and Technology, Trichy, India

Abstract


A Simulated Annealing (SA) based optimization procedure has been developed to optimize grinding conditions viz. wheel speed, workpiece speed, depth of dressing and lead of dressing, using multi-objective function model with a weighted approach for surface grinding process. The procedure evaluates the production cost, production rate and surface finish for optimum grinding conditions, subjected to thermal damage, wheel-wear parameter, machine-tool stiffness and surface finish or production rate constraints. A computer program written in Visual C++ has been developed for optimization computations. The program prompts the user to input or modify all the constants related to the grinding operations. All the constants used here are default values, unless over-written by the user. User can also alter the specific Input values to perform sensitivity analysis of the relative contributions of grinding parameters to the weighted objective function. Simulated Annealing (SA) optimization is illustrated with an example and the optimum results are compared with Quadratic programming and Genetic Algorithm techniques.