期刊
JOURNAL OF INTELLIGENT MANUFACTURING
卷 25, 期 6, 页码 1463-1472出版社
SPRINGER
DOI: 10.1007/s10845-013-0753-y
关键词
Machining; Abrasive waterjet; Optimization
资金
- Research Management Centre
- UTM and Ministry of Higher Education Malaysia (MOHE)
- Exploratory Research Grant Scheme (ERGS) [Q.J13000078284L003]
Modern machining processes such as abrasive waterjet (AWJ) are widely used in manufacturing industries nowadays. Optimizing the machining control parameters are essential in order to provide a better quality and economics machining. It was reported by previous researches that artificial bee colony (ABC) algorithm has less computation time requirement and offered optimal solution due to its excellent global and local search capability compared to the other optimization soft computing techniques. This research employed ABC algorithm to optimize the machining control parameters that lead to a minimum surface roughness (R-a) value for AWJ machining. Five machining control parameters that are optimized using ABC algorithm include traverse speed (V), waterjet pressure (P), standoff distance (h), abrasive grit size (d) and abrasive flow rate (m). From the experimental results, the performance of ABC was much superior where the estimated minimum R-a value was 28, 42, 45, 2 and 0.9% lower compared to actual machining, regression, artificial neural network (ANN), genetic algorithm (GA) and simulated annealing (SA) respectively.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据