论文信息 - Multi-objective optimisation of surface grinding operations using scatter search approach

Multi-objective optimisation of surface grinding operations using scatter search approach

A scatter search based optimisation approach is developed to optimise the grinding parameters of wheel speed, work piece speed, depth of dressing and lead of dressing using a multi-objective function model with a weighted approach for the surface grinding process. The production cost and production rate are evaluated for the optimal grinding conditions, subject to the constraints such as thermal damage, machine tool stiffness, wheel wear parameters and surface finish. The results are compared with the results obtained by the ants-colony algorithm, genetic algorithm and quadratic programming techniques.

Alluru Gopala Krishna | K. Mallikarjuna Rao

[1] Riccardo Poli,et al. New ideas in optimization , 1999 .

[2] T. Warren Liao,et al. A neural network approach for grinding processes: Modelling and optimization , 1994 .

[3] R. Saravanan,et al. A multi-objective genetic algorithm (GA) approach for optimization of surface grinding operations , 2002 .

[4] Stephen Malkin,et al. Thermal Aspects of Grinding: Part 2—Surface Temperatures and Workpiece Burn , 1974 .

[5] Yoram Koren,et al. ADAPTIVE CONTROL OPTIMIZATION OF GRINDING. , 1981 .

[6] O. F. Devereux,et al. Handbook of Modern Grinding Technology , 1987 .

[7] R. A. Thompson. The Dynamic Behavior of Surface Grinding: Part 1—A Mathematical Treatment of Surface Grinding , 1971 .

[8] Li Yan,et al. Applications of artificial intelligence in grinding , 1994 .

[9] F. Glover. Scatter search and path relinking , 1999 .

[10] G. J. Trmal,et al. Optimum selection of grinding parameters using process modelling and knowledge based system approach , 1991 .

[11] F. Glover,et al. Fundamentals of Scatter Search and Path Relinking , 2000 .

[12] S. Malkin. Selection of Operating Parameters in Surface Grinding of Steels , 1976 .

[13] Andrew Y. C. Nee,et al. Micro-computer-based optimization of the surface grinding process , 1992 .

[14] R. Saravanan,et al. Ants colony algorithm approach for multi-objective optimisation of surface grinding operations , 2004 .