5 / 2018-02-23 11:30:13
Numerical modeling on the cost effectiveness of visual defects rejection methodology applied in Automotive IC testing
cost effectiveness of visual defects rejection methodology,Automotive IC testing
Draft Pending
Lee Mun Loong / STMicroelectronics
Alagappan Narayanan / STMicroelectronics
Villari Vittorio / STMicroelectronics
Zhang Ping / STMicroelectronics
Lin Shi Zhe / National University of Singapore
Phua Rui Qing / Nanyang Technological University
Automotive IC suppliers are expected to ship devices with zero PPM (zero failure per million devices) to the system manufacturers with sustainable yield. Yield is the key performance indicator measuring the cost structure of the semiconductor fabrication process. Semiconductor yield modeling which is a complicated task, is related to identifying process issues, improving quality and adhering to the market quality field performance request. It is a complicated process because it is difficult to link any internal process improvement and PPM level due to elapsed time, different magnitude and not easy to access the field data. Therefore, any economic analysis of balancing the cost of improvement versus the benefit is seen usually as weak if not impossible. This paper address a specific improvement action but the methodology can be applied broadly. This paper presents modeling strategies based on the rejection of visual defects methodology. Through data consolidation and analysis, the key achievement is to be able to validate data with the theoretical model and also to understand the correlation among the main factors that affect the yield. Hence the efficiency and the effectiveness of testing process become predictable. Therefore, analysis and evaluation of the impact on reliability and cost effectiveness could be made possible.
Important Date
  • Conference Date

    Oct 30



    Nov 03


  • Feb 24 2018

    Abstract Submission Deadline

  • Mar 24 2018

    Draft paper submission deadline

  • Jun 05 2018

    Draft Paper Acceptance Notification

  • Jul 24 2018

    Final Paper Deadline

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