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Open AccessArticle

Improving Electronic Sensor Reliability by Robust Outlier Screening

Freescale® Semiconductor Inc., 6501 William Cannon Dr., Austin, TX 78735, USA
Escuela Técnica Superior de Ingeniería, University of Seville, Camino de los Descubrimientos s/n, Seville E-41092, Spain
Author to whom correspondence should be addressed.
Sensors 2013, 13(10), 13521-13542;
Received: 16 August 2013 / Revised: 24 September 2013 / Accepted: 25 September 2013 / Published: 9 October 2013
(This article belongs to the Special Issue Modeling, Testing and Reliability Issues in MEMS Engineering 2013)
Electronic sensors are widely used in different application areas, and in some of them, such as automotive or medical equipment, they must perform with an extremely low defect rate. Increasing reliability is paramount. Outlier detection algorithms are a key component in screening latent defects and decreasing the number of customer quality incidents (CQIs). This paper focuses on new spatial algorithms (Good Die in a Bad Cluster with Statistical Bins (GDBC SB) and Bad Bin in a Bad Cluster (BBBC)) and an advanced outlier screening method, called Robust Dynamic Part Averaging Testing (RDPAT), as well as two practical improvements, which significantly enhance existing algorithms. Those methods have been used in production in Freescale® Semiconductor probe factories around the world for several years. Moreover, a study was conducted with production data of 289,080 dice with 26 CQIs to determine and compare the efficiency and effectiveness of all these algorithms in identifying CQIs. View Full-Text
Keywords: semiconductor device testing; zero defect; customer quality incident; robust statistics semiconductor device testing; zero defect; customer quality incident; robust statistics
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Moreno-Lizaranzu, M.J.; Cuesta, F. Improving Electronic Sensor Reliability by Robust Outlier Screening. Sensors 2013, 13, 13521-13542.

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