Yield Process Control based on the Production Data

Nhan D. Truong, Serge N. Demidenko, Giovanni M. Merola

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

1 Citation (Scopus)


Semiconductor device manufacturing process involves a large number of sophisticated production steps that have to be controlled precisely so to achieve and to maintain the required yield and product quality specifications. Therefore, it is critical to employ extensive data collection from numerous process-associated sensors. The data are then utilized by the process control system (PCS) to monitor and control the manufacturing process. This paper presents a real-world study performed at one of the major semiconductor device manufacturers where the massive data from the production line sensors were analyzed by PCS to (1) determine parameters that are significantly correlated with the product yield; and (2) perform a regression analysis to estimate the yield from PCS data. The study enabled to identify several key parameters, that can be optimized to improve the product yield.

Original languageEnglish
Title of host publication2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728148427
Publication statusPublished - Mar 2020
Event15th IEEE Sensors Applications Symposium, SAS 2020 - Kuala Lumpur, Malaysia
Duration: 9 Mar 202011 Mar 2020

Publication series

Name2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings


Conference15th IEEE Sensors Applications Symposium, SAS 2020
CityKuala Lumpur


  • manufacturing
  • process control system
  • regression analysis
  • yield

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