For many industrial machining operations, the quality of surface finish is the prominent requirement. Nevertheless the selection of optimized cutting parameters is very essential for controlling the desired surface quality. Main aim of this attempt is to fix the set of cutting parameters combinations using optimization algorithms. Ant Colony algorithm, Scatter Search algorithm, Genetic algorithm and BAT algorithm were used for various parameters on the surface roughness to arrive a suitable combination of parameters which are optimal to meet the product quality requirement. The effectiveness of the algorithms is ordered based up on the error rate while computing and the best two algorithms are combined for more tuned outcome
Surface roughness, an indicator of surface quality is one of the most specified customer requirement...
Since cutting conditions have an influence on reducing the production cost and time and deciding the...
An optimization paradigm based on genetic algorithms (GA) for the determination of the cutting param...
The aim of present research focuses on the prediction of machining parameters that improve the quali...
In finishing end milling, not only good accuracy but also good roughness levels must be achieved. Th...
AbstractParametric optimization of turning process is a multi-objective optimization task. In genera...
The determination of optimal cutting parameters have significant importance for economic machining i...
In highly competitive manufacturing industries nowadays, the manufactures ultimate goals are to prod...
AbstractAn optimization paradigm based on genetic algorithms (GA) for the determination of the cutti...
AbstractThis paper develops a predictive and optimization model by coupling the two artificial intel...
AbstractIn the present study, response surface methodology has been applied to determine the optimum...
Optimal selection of cutting parameters is one of the significant issues in achieving high quality m...
An optimization paradigm based on genetic algorithms (GA) for the determination of the cutting param...
The optimization process is applied to the machining operations in order to provide continual improv...
An optimization paradigm based on genetic algorithms (GA) for the determination of the cutting param...
Surface roughness, an indicator of surface quality is one of the most specified customer requirement...
Since cutting conditions have an influence on reducing the production cost and time and deciding the...
An optimization paradigm based on genetic algorithms (GA) for the determination of the cutting param...
The aim of present research focuses on the prediction of machining parameters that improve the quali...
In finishing end milling, not only good accuracy but also good roughness levels must be achieved. Th...
AbstractParametric optimization of turning process is a multi-objective optimization task. In genera...
The determination of optimal cutting parameters have significant importance for economic machining i...
In highly competitive manufacturing industries nowadays, the manufactures ultimate goals are to prod...
AbstractAn optimization paradigm based on genetic algorithms (GA) for the determination of the cutti...
AbstractThis paper develops a predictive and optimization model by coupling the two artificial intel...
AbstractIn the present study, response surface methodology has been applied to determine the optimum...
Optimal selection of cutting parameters is one of the significant issues in achieving high quality m...
An optimization paradigm based on genetic algorithms (GA) for the determination of the cutting param...
The optimization process is applied to the machining operations in order to provide continual improv...
An optimization paradigm based on genetic algorithms (GA) for the determination of the cutting param...
Surface roughness, an indicator of surface quality is one of the most specified customer requirement...
Since cutting conditions have an influence on reducing the production cost and time and deciding the...
An optimization paradigm based on genetic algorithms (GA) for the determination of the cutting param...