Applying Fuzzy Neural Networks and Gray Theory to Construct a Modular Product Customization System

被引：0

作者：

Chen, Miao-Sheng ^{[1
]}

Hung, Fei-Kung ^{[1
]}

机构：

[1] Nanhua Univ, Dept Business Adm, Chiayi, Taiwan

来源：

MANUFACTURING SCIENCE AND ENGINEERING, PTS 1-5 | 2010年 / 97-101卷

关键词：

Modular products; Neural network; Gray theory; Fuzzy theory; Analytic hierarchy process; Customization; COLOR DESIGN; SELECTION;

D O I：

10.4028/www.scientific.net/AMR.97-101.3722

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This research establishes a "Customized modular product system". Modular products can be defined according to their different functions and components. To build the learning and searching evaluation model of this system, the back-propagation neural networks and gray theory were used. Besides, Fuzzy theory and analytic hierarchy process were also utilized to model the relation and evaluation algorithms. In this way, it can provide neural networks with basic learning rules and a training samples. Based on different degrees of the consumer demand, the proposed method in this research performs the optimal module-combination for modular products. It will guide the customers to select the most suitable modular product group. Additionally, through the study case of the baby stroller manufacturing company, how to achieve the purpose of customization can be illustrated.

引用

页码：3722 / 3726

页数：5

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