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Reliability predictions for high density packaging

Reliability predictions for high density packaging

Bailey, C. ORCID logoORCID: https://orcid.org/0000-0002-9438-3879, Stoyanov, S. ORCID logoORCID: https://orcid.org/0000-0001-6091-1226 and Lu, H. ORCID logoORCID: https://orcid.org/0000-0002-4392-6562 (2004) Reliability predictions for high density packaging. In: Proceeding of The Sixth IEEE CPMT Conference on High Density Microsystem Design and Packaging and Component Failure Analysis (HDP'04). Institute of Electrical and Electronics Engineers, Inc., Piscataway, N.J., U.S.A., pp. 121-128. ISBN 0780386205 (doi:10.1109/HPD.2004.1346684)

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Abstract

Predicting the reliability of newly designed products, before manufacture, is obviously highly desirable for many organisations. Understanding the impact of various design variables on reliability allows companies to optimise expenditure and release a package in minimum time. Reliability predictions originated in the early years of the electronics industry. These predictions were based on historical field data which has evolved into industrial databases and specifications such as the famous MIL-HDBK-217 standard, plus numerous others. Unfortunately the accuracy of such techniques is highly questionable especially for newly designed packages. This paper discusses the use of modelling to predict the reliability of high density flip-chip and BGA components. A number of design parameters are investigated at the assembly stage, during testing, and in-service.

Item Type: Conference Proceedings
Title of Proceedings: Proceeding of The Sixth IEEE CPMT Conference on High Density Microsystem Design and Packaging and Component Failure Analysis (HDP'04)
Additional Information: [1] This paper was first presented at the Sixth IEEE CPMT Conference on High Density Microsystem Design and Packaging and Component Failure Analysis (HDP'04) held from 30 June - 3 July 2004 in Shanghai, China.
Uncontrolled Keywords: ball grid arrays, flip-chip devices, packaging, semiconductor device reliability
Subjects: Q Science > QA Mathematics > QA76 Computer software
T Technology > T Technology (General)
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis > Computational Mechanics & Reliability Group
School of Computing & Mathematical Sciences > Department of Computer Systems Technology
School of Computing & Mathematical Sciences > Department of Mathematical Sciences
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Last Modified: 20 Mar 2019 11:54
URI: http://gala.gre.ac.uk/id/eprint/772

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