首页> 外文会议>Computers and information in engineering conference >A KNOWLEDGE DISCOVERY IN DATABASES (KDD) APPROACH FOR EXTRACTING CAUSES OF ITERATIONS IN ENGINEERING CHANGE ORDERS
【24h】

A KNOWLEDGE DISCOVERY IN DATABASES (KDD) APPROACH FOR EXTRACTING CAUSES OF ITERATIONS IN ENGINEERING CHANGE ORDERS

机译:数据库中的知识发现(KDD)方法,用于在工程变更订单中提取迭代原因的方法

获取原文

摘要

This paper describes an implementation of a Knowledge Discovery in Databases (KDD) process for extracting the causes of iterations in Engineering Change Orders (ECOs). A data set of approximately 53,000 historical Engineering Change Orders (ECOs) was used for this purpose. Initially, the impact of iterations in ECO lead time and uncertainty is assessed. Subsequently, a semi-automatic text-mining process is employed to classify the causes of iterations. As a result, cost and technical categories of causes were identified as the main reasons for the occurrence of iterations. The study concludes that applying KDD in historic ECO data can help in identifying the causes of iterations of ECO which subsequently can provide a framework for companies to reduce these iterations. In addition, the case represents an example of benefits that can be achieved with the application of KDD in engineering change management.
机译:本文介绍了数据库中知识发现的实现,用于提取工程变更订单(ECO)中的迭代原因。为此目的使用了大约53,000名历史工程变更订单(ECO)的数据集。最初,评估迭代在Eco报告时间和不确定性中的影响。随后,采用半自动文本挖掘过程来对迭代的原因进行分类。因此,成本和技术类别的原因被确定为迭代发生的主要原因。该研究的结论是,在历史悠久的生态数据中应用KDD可以帮助确定ECO迭代的原因,随后可以为公司提供框架来减少这些迭代。此外,案例代表了在工程变革管理中应用KDD可以实现的益处的一个例子。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号