Computer-Aided Genetic Algorithm Based Multi-Objective Optimization of Laser Trepan Drilling

被引：32
|
作者：
Kumar, Sanjay [1 ]
Dubey, Avanish Kumar [1 ]
Pandey, Arun Kumar [1 ]
机构：
[1] Motilal Nehru Natl Inst Technol, Dept Mech Engn, Allahabad 211004, Uttar Pradesh, India
来源：
INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING | 2013年 / 14卷 / 07期
关键词：
Laser trepan drilling; Recast layer thickness; Regression analysis; Genetic algorithm; Multi-objective optimization; NEURAL-NETWORK; QUALITY; RECAST;
D O I：
10.1007/s12541-013-0152-5
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The laser trepan drilling (LTD) has proven to produce better quality holes in advanced materials as compared with laser percussion drilling (LPD). But due to thermal nature of LTD process, it is rarely possible to completely remove the undesirable effects such as recast layer, heat affected zone and micro cracks. In order to improve the hole quality, these effects are required to be minimized. This research paper presents a computer-aided genetic algorithm-based multi-objective optimization (CGAMO) methodology for simultaneous optimization of multiple quality characteristics. The optimization results of the software CGAMO has been tested and validated by the published literature. Further, CGAMO has been used to simultaneously optimize the recast layer thickness (RLT) at entrance and exit in LTD of nickel based superalloy sheet. The predicted results show minimization of 99.82% and 85.06% in RLT at entrance and exit, respectively The effect of significant process parameters on RLT has also been discussed.
引用
收藏
页码：1119 / 1125
页数：7
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