Title :
An overview of GA technique for surface roughness optimization in milling process
Author :
Zain, Azlan Mohd ; Haron, Habibollah ; Sharif, Safian
Author_Institution :
Faculty of Computer Science & Information System, Universiti Teknologi Malaysia, Skudai Johor, Malaysia
Abstract :
Optimization of parameters in machining is a nonlinear model with constraints, so it is difficult to be conducted using conventional approaches. As alternative, non conventional approaches become useful approaches to conduct machining parameter optimization problem. Genetic Algorithm (GA) is one of the well known techniques classified as non conventional approaches with intelligent in human behavior that is mostly applied to ensure efficient and fast selection of the optimum cutting conditions for parameters in machining process. This paper outlines an understanding of how GA system operates in order to optimize the surface roughness performance measure in milling process. Example of works that applied GA technique for machining optimizing problem for surface roughness is also given.
Keywords :
Computer science; Constraint optimization; Genetic algorithms; Information systems; Machining; Mathematical model; Milling; Predictive models; Rough surfaces; Surface roughness;
Conference_Titel :
Information Technology, 2008. ITSim 2008. International Symposium on
Conference_Location :
Kuala Lumpur, Malaysia
Print_ISBN :
978-1-4244-2327-9
Electronic_ISBN :
978-1-4244-2328-6
DOI :
10.1109/ITSIM.2008.4631925