Implementing a data mining solution for enhancing carpet manufacturing productivity

被引：27

作者：

Ciflikli, Cebrail ^{[1
]}

Kahya-Ozyirmidokuz, Esra ^{[1
]}

机构：

[1] Erciyes Univ, Kayseri Vocat Coll, Kayseri, Turkey

来源：

KNOWLEDGE-BASED SYSTEMS | 2010年 / 23卷 / 08期

关键词：

Data mining; Knowledge discovery in databases; Decision trees; Rule induction; Attribute relevance analysis; ALGORITHM; INDUSTRY; QUALITY; SYSTEMS; SUPPORT;

D O I：

10.1016/j.knosys.2010.05.001

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In recent years, knowledge has received significant attention in manufacturing to built a competitive advantage in the sector. Knowledge induction from data is an important issue in manufacturing to find the failure of the process then predict and improve the future system performance. This research examines the improvement of manufacturing process via data mining. Not only do we detect and isolate machine breakdowns in carpet manufacturing, but also we propose a C4.5 decision tree model. In addition, we use attribute relevance analysis to select the qualitative attribute's variables. Consequently, manufacturing process is redeveloped. (C) 2010 Elsevier B.V. All rights reserved.

引用

页码：783 / 788

页数：6

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