@inproceedings{b2d2c4a492344151bc01f89982d79736,
title = "Eliminating Re-Burn-In in semiconductor manufacturing through statistical analysis of production test data",
abstract = "Zero Re-Burn-In methodology presented in this paper is based on statistical analysis of the historical manufacturing data on burn-in (BI) and re-burn-in (REBI) tests employed in semiconductor devices manufacturing. The goal is to reduce (or, if possible, to eliminate) REBI test so to lower the associated manufacturing cost and time while preserving the required low failure rate of the manufactured devices. The statistical processing and analysis of the production data sets are performed while employing the JMP software. The re-search has led to development of a logistic regression model capable of predicting results of the REBI tests before actually sending integrated circuit (IC) lots for the re-testing.",
keywords = "Burn in test, Integrated circuit, Logistic regression model, Manufacturing, Probability, Statistical analysis",
author = "Pham, {Hung V.} and Demidenko, {Serge N.} and Merola, {Giovanni M.}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2017 ; Conference date: 22-05-2017 Through 25-05-2017",
year = "2017",
month = jul,
day = "5",
doi = "10.1109/I2MTC.2017.7969957",
language = "English",
series = "I2MTC 2017 - 2017 IEEE International Instrumentation and Measurement Technology Conference, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "I2MTC 2017 - 2017 IEEE International Instrumentation and Measurement Technology Conference, Proceedings",
}