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008 090710t2008 my a f m 000 0 eng d
020 _aTHE0006520(Local)
039 9 _a201905141450
_bamirul
_c201107132151
_dVLOAD
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_dVLOAD
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_y200907101205
_zkam
040 _aUMP
090 _aTJ1185 .S53 2008 rs Bc.
100 0 _aShah Izwandi Mohd Zawawi
245 1 0 _aOptimization of turning parameters using genetic algorithm method /
_cShah Izwandi Bin Mohd Zawawi
246 3 _aOptimization of turning parameters using genetic algorithm method
_h[electronic resource]
260 _aKuantan, Pahang :
_bUMP,
_c2008
300 _a62, 16, 2 p. :
_bill. (some col.) ;
_c30 cm. +
_e1 computer disc
502 _aProject paper (Bachelor of Mechanical Engineering with Manufacturing Engineering) -- Universiti Malaysia Pahang - 2008
520 _aThis study about development of optimization for turning parameters based on the Genetic Algorithm (GA). This method was demonstrated for the optimization of machining parameters for turning operation using conventional lathe machines. Currently, everybody has start realizing the importance of this new manufacturing optimization in order to improve the performance and its efficiency. The purpose of this project is to find the optimum parameters values for turning operations that will benefit such as reduces the machining time, improves their quality and productivity and also minimize the unit cost of the product. GA can be used in optimization problems such as scheduling, materials engineering , optimal control, and so forth. This approach has led to the important following discoveries such as GA has robustness, the balance between efficiency and performances for survival in many different environments. The machining parameters that been consider in this thesis are cutting speed, feed rate and depth of cut. The GA simulation are been develop to achieve the objective. The MATLAB software will be use to develop the GA simulation. An example to apply the Genetic Algorithm to the problem has been presented at the end of this paper to give more understanding picture from the application of the system and how its work. The result obtained from this simulation shown GA has a potential for improvements in order to optimize the turning parameters and minimize the unit production cost. The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.
650 0 _aMachining
999 _aVIRTUA40
_c1182
_d1188
999 _aVTLSSORT0080*0200*0400*0900*1000*2450*2460*2600*3000*5020*5200*6500*9992