Application of genetic algorithm to computer-aided process planning in distributed manufacturing environments

被引：77

作者：

Li, L ^{[1
]}

Fuh, JYH ^{[1
]}

Zhang, YF ^{[1
]}

Nee, AYC ^{[1
]}

机构：

[1] Natl Univ Singapore, Dept Engn Mech, Singapore 117576, Singapore

来源：

ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING | 2005年 / 21卷 / 06期

关键词：

computer-aided process planning; distributed manufacturing system; multiple factories; genetic algorithm;

D O I：

10.1016/j.rcim.2004.12.003

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In a distributed manufacturing environment, factories possessing various machines and tools at different geographical locations are often combined to achieve the highest production efficiency. When jobs requiring several operations are received, feasible process plans are produced by those factories available. These process plans may vary due to different resource constraints. Therefore, obtaining an optimal or near-optimal process plan becomes important. This paper presents a genetic algorithm (GA), which, according to prescribed criteria such as minimizing processing time, could swiftly search for the optimal process plan for a single manufacturing system as well as distributed manufacturing systems. By applying the GA, the computer-aided process planning (CAPP) system can generate optimal or near-optimal process plans based on the criterion chosen. Case studies are included to demonstrate the feasibility and robustness of the approach. The main contribution of this work lies with the application of GA to CAPP in both a single and distributed manufacturing system. It is shown from the case study that the approach is comparative or better than the conventional single-factory CAPP. (c) 2005 Elsevier Ltd. All rights reserved.

引用

页码：568 / 578

页数：11

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