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003 KUKTEM
005 20251114204418.0
008 090708t2008 my a f m 00| 0 eng|d
020 _aTHE0006561(Local)
039 9 _a201905161002
_bamirul
_c201905161002
_damirul
_c201107132244
_dVLOAD
_c200908141645
_dVLOAD
_y200907081010
_zida84
040 _aUMP
090 _aTJ1189 .S28 2008 rs Bc.
100 0 _aMohd Saupi Mohd Sauki
245 1 0 _aOptimization of milling parameters using ant colony optimization /
_cMohd Saupi Mohd Sauki
246 3 _aOptimization of milling parameters using ant colony optimization
_h[electronic resource]
260 _aKuantan, Pahang :
_bUMP,
_c2008
300 _a63 p. :
_bill. ;
_c30 cm. +
_e1 computer disc
502 _aProject paper (Bachelor of Mechanical Engineering with Manufacturing) -- Universiti Malaysia Pahang - 2008
520 3 _aIn process planning of conventional milling, selecting reasonable milling parameters is necessary to satisfy requirements involving machining economics, quality and safety. This study is to develop optimization procedures based on the Ant Colony Optimization (ACO). This method was demonstrated for the optimization of machining parameters for milling operation. The machining parameters in milling operations consist of cutting speed, feed rate and depth of cut. These machining parameters significantly impact on the cost, productivity and quality of machining parts. The developed strategy based on the maximize production rate criterion. This study describes development and utilization of an optimization system, which determines optimum machining parameters for milling operations. The ACO simulation is develop to achieve the objective to optimize milling parameters to maximize the production rate in milling operation. The Matlab software will be use to develop the ACO simulation. All the references are taken from related articles, journals and books. An example to apply the Ant Colony Algorithm to the problem has been presented at the end of the paper to give clear picture from the application of the system and its efficiency. The result obtained from this simulation will compare with another method like Genetic Algorithm (GA) and Linear Programming Technique (LPT) to validation. The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation
650 0 _aMachine-tools
_xNumerical control
650 0 _aMachine-tools
_xProgrammning
999 _aVIRTUA40
_c1587
_d1593
999 _aVTLSSORT0080*0200*0400*0900*1000*2450*2460*2600*3000*5020*5200*6500*6501*9992