Eliminating Re-Burn-In in semiconductor manufacturing through statistical analysis of production test data

Pham, H, Demidenko, S and Merola, G 2017, 'Eliminating Re-Burn-In in semiconductor manufacturing through statistical analysis of production test data', in IEEE International Instrumentation and Measurement Technology Conference (I2MTC 2017), Turin, Italy, 22 May 2017, pp. 1-6.


Document type: Conference Paper
Collection: Conference Papers

Title Eliminating Re-Burn-In in semiconductor manufacturing through statistical analysis of production test data
Author(s) Pham, H
Demidenko, S
Merola, G
Year 2017
Conference name IEEE International Instrumentation and Measurement Technology Conference (I2MTC 2017)
Conference location Turin, Italy
Conference dates 22 May 2017
Proceedings title IEEE International Instrumentation and Measurement Technology Conference (I2MTC 2017)
Publisher IEEE
Place of publication United States
Start page 1
End page 6
Total pages 6
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 research 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.
Subjects Microelectronics and Integrated Circuits
Keyword(s) Statistical analysis
Logistic regression model
Burn in test
Probability
Integrated circuit
Manufacturing
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ISBN 1509035966
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