GENETIC ALGORITHM-BASED OPTIMIZATION FOR SURFACE ROUGHNESS IN CYLINDRICALLY GRINDING PROCESS USING HELICALLY GROOVED WHEELS

被引：1
|
作者：
Caydas, Ulas [1 ]
Celik, Mahmut [1 ]
机构：
[1] Firat Univ, Technol Fac, Dept Mech Engn, TR-23119 Elazig, Turkey
来源：
SURFACE REVIEW AND LETTERS | 2017年 / 24卷
关键词：
Grinding; surface; roughness; optimization; machining; MACHINING PARAMETERS; EDM PROCESS; METHODOLOGY; DESIGN; LAYER;
D O I：
10.1142/S0218625X18500312
中图分类号：
O64 [物理化学（理论化学）、化学物理学];
学科分类号：
070304 ; 081704 ;
摘要：
The present work is focused on the optimization of process parameters in cylindrical surface grinding of AISI 1050 steel with grooved wheels. Response surface methodology (RSM) and genetic algorithm (GA) techniques were merged to optimize the input variable parameters of grinding. The revolution speed of workpiece, depth of cut and number of grooves on the wheel were changed to explore their experimental effects on the surface roughness of machined bars. The mathematical models were established between the input parameters and response by using RSM. Then, the developed RSM model was used as objective functions on GA to optimize the process parameters.
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页数：8
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