Developing a product quality fault detection scheme

Yi Ting Huang, Fan Tien Cheng, Min Hsiung Hung

研究成果: Conference contribution

9 引文 斯高帕斯(Scopus)

摘要

In current semiconductor and TFT-LCD factories, periodic sampling is commonly adopted to monitor the stability of manufacturing processes and the quality of products (or workpieces). As for those non-sampled workpieces, their quality is usually monitored by such as a fault-detection-and-classification (FDC) server. However, this method may fail to detect defected products. For example, a workpiece with all the individual manufacturing process parameters being in-spec may still result in out-of-spec product quality. Under this circumstance, unless this certain defected workpiece is selected for sampling by chance, it cannot be detected by simply monitoring the manufacturing process parameters collected from the production equipment. To solve the abovementioned problem, this research proposes a product quality fault detection scheme (FDS), which utilizes the classification and regression tree to implement a model for identifying the relationship between process parameters and out-of-spec products. Through this model, each set of normal manufacturing process parameters can be real-time and on-line examined to detect failure or defected products.

原文English
主出版物標題2009 IEEE International Conference on Robotics and Automation, ICRA '09
頁面927-932
頁數6
DOIs
出版狀態Published - 2009 十一月 2
事件2009 IEEE International Conference on Robotics and Automation, ICRA '09 - Kobe, Japan
持續時間: 2009 五月 122009 五月 17

出版系列

名字Proceedings - IEEE International Conference on Robotics and Automation
ISSN(列印)1050-4729

Other

Other2009 IEEE International Conference on Robotics and Automation, ICRA '09
國家/地區Japan
城市Kobe
期間09-05-1209-05-17

All Science Journal Classification (ASJC) codes

  • 軟體
  • 控制與系統工程
  • 人工智慧
  • 電氣與電子工程

指紋

深入研究「Developing a product quality fault detection scheme」主題。共同形成了獨特的指紋。

引用此