Automatic detection of failure patterns using data mining

被引:0
|
作者
Han, Y [1 ]
Kim, J [1 ]
Lee, C [1 ]
机构
[1] Sungkyunkwan Univ, Sch Informat & Commun Engn, Suwon 440746, Kyunggi Do, South Korea
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In the semiconductor manufacturing, yield enhancement is an important issue. It is ideal to prevent all failures, However, when a failure occurs, it is important to quickly specify the cause stage and take countermeasures. Reviewing wafer level and composite lot level yield patterns has always been an effective way of identifying yield inhibitors and driving process improvement. This process is very time consuming and as such generally occurs only when the overall yield of a device has dropped significantly enough to warrant investigation. The automatic method of failure pattern extraction from fail bit map provides reduced time to analysis and facilitates yield enhancement. The automatic method of failure pattern extraction from fail bit map provides reduced time to analysis and facilitates yield enhancement. This paper describes the techniques to automatically recognize and classifies a failure pattern using a fail bit map, a new simple schema which facilitates the failure analysis.
引用
收藏
页码:1312 / 1316
页数:5
相关论文
共 50 条
  • [1] Automatic detection of interictal spikes using data mining models
    Valenti, P
    Scarpettini, M
    Cazamajou, E
    Aizemberg, A
    Silva, W
    Giagante, B
    Oddo, S
    Kochen, S
    EPILEPSIA, 2003, 44 : 179 - 179
  • [2] Automatic detection of interictal spikes using data mining models
    Valenti, P
    Cazamajou, E
    Scarpettini, M
    Aizemberg, A
    Silva, W
    Kochen, S
    JOURNAL OF NEUROSCIENCE METHODS, 2006, 150 (01) : 105 - 110
  • [3] Automatic brain tumour detection using image processing and data mining techniques
    Ramani R.G.
    Faustina F.
    Siddique S.
    Sivaselvi K.
    International Journal of Information Technology and Management, 2021, 20 (1-2) : 49 - 65
  • [4] Automatic database clustering using data mining
    Guinepain, Sylvain
    Gruenwald, Le
    SEVENTEENTH INTERNATIONAL CONFERENCE ON DATABASE AND EXPERT SYSTEMS APPLICATIONS, PROCEEDINGS, 2006, : 124 - +
  • [5] A novel automatic satire and irony detection using ensembled feature selection and data mining
    Ravi, Kumar
    Ravi, Vadlamani
    KNOWLEDGE-BASED SYSTEMS, 2017, 120 : 15 - 33
  • [6] Automatic Detection of Diabetic Retinopathy using Image Processing and Data Mining Techniques.
    Argade, Ketki S.
    Deshmukh, Kshitija A.
    Narkhede, Madhura M.
    Sonawane, Nayan N.
    Jore, Sandeep
    2015 International Conference on Green Computing and Internet of Things (ICGCIoT), 2015, : 517 - 521
  • [7] Intrusion detection using data mining
    Puthran, Shubha
    Shah, Ketan
    Puthran, Shubha (shubha.puthran@nmims.edu), 1600, Inderscience Publishers (09): : 292 - 306
  • [8] Detection of Desertion Patterns in University Students Using Data Mining Techniques: A Case Study
    Vila, Dayana
    Cisneros, Saul
    Granda, Pedro
    Ortega, Cosme
    Posso-Yepez, Miguel
    Garcia-Santillan, Ivan
    TECHNOLOGY TRENDS, 2019, 895 : 420 - 429
  • [9] Mining constraint-based patterns using automatic relaxation
    Soulet, Arnaud
    Cremilleux, Bruno
    INTELLIGENT DATA ANALYSIS, 2009, 13 (01) : 109 - 133
  • [10] Automatic Detection and Correction of Web Application Vulnerabilities using Data Mining to Predict False Positives
    Medeiros, Iberia
    Neves, Nuno F.
    Correia, Miguel
    WWW'14: PROCEEDINGS OF THE 23RD INTERNATIONAL CONFERENCE ON WORLD WIDE WEB, 2014, : 63 - 73