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Sintered silver finite element modelling and reliability based design optimisation in power electronic module

Sintered silver finite element modelling and reliability based design optimisation in power electronic module

Rajaguru, Pushparajah ORCID: 0000-0002-6041-0517, Lu, Hua ORCID: 0000-0002-4392-6562 and Bailey, Chris ORCID: 0000-0002-9438-3879 (2015) Sintered silver finite element modelling and reliability based design optimisation in power electronic module. Microelectronics Reliability, 55 (6). pp. 919-930. ISSN 0026-2714 (doi:https://doi.org/10.1016/j.microrel.2015.03.011)

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Abstract

This paper discusses the design for reliability of a sintered silver structure in a power electronic module based on the computational approach that composed of high fidelity analysis, reduced order modelling, numerical risk analysis, and optimisation. The methodology was demonstrated on sintered silver interconnect sandwiched between silicon carbide chip and copper substrate in a power electronic module. In particular, sintered silver reliability due to thermal fatigue material degradation is one of the main concerns. Thermo-mechanical behaviour of the power module sintered silver joint structure is simulated by finite element analysis for cyclic temperature loading profile in order to capture the strain distribution. The discussion was on methods for approximate reduced order modelling based on interpolation techniques using Kriging and radial basis functions. The reduced order modelling approach uses prediction data for the thermo-mechanical behaviour. The fatigue lifetime of the sintered silver interconnect and the warpage of the interconnect layer was particular interest in this study. The reduced order models were used for the analysis of the effect of design uncertainties on the reliability of the sintered silver layer. To assess the effect of uncertain design data, a method for estimating the variation of reliability related metrics namely Latin Hypercube sampling was utilised. The product capability indices are evaluated from the distributions fitted to the histogram resulting from Latin Hypercube sampling technique. A reliability based design optimisation was demonstrated using Particle Swarm Optimisation algorithm for constraint optimisation task consists of optimising two different characteristic performance metrics such as the thermo-mechanical plastic strain accumulation per cycle on the sintered layer and the thermally induced warpage.

Item Type: Article
Additional Information: [1] The Author's Accepted Manuscript version has been uploaded in accordance with the publisher's self-archiving policy. This is the Author's Accepted Manuscript version, uploaded in accordance with the publisher's self-archiving policy. Please note: this is the author’s version of a work that was accepted for publication in MICROELECTRONICS RELIABILITY. Changes resulting from the publishing process, such as editing, structural formatting, and other quality control mechanisms may not be reflected in this document. The definitive version is available at: http://dx.doi.org/10.1016/j.microrel.2015.03.011. [2] Acknowledgements (funding): Financial support from the Engineering and Physical Sciences Research Council (EPSRC), UK and Innovative electronic Manufacturing Research Centre (IeMRC Project Number: SP/03/02/11) funded project namely Robustness Design and Health Management in Power Electronic using Damage Mechanics based Models (RODENT) is acknowledged.
Uncontrolled Keywords: reduced order models, power electronic module, risk analysis, Particle Swarm Optimisation, Kriging, radial basis
Subjects: Q Science > QA Mathematics
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Faculty of Architecture, Computing & Humanities > Centre for Numerical Modelling & Process Analysis (CNMPA)
Faculty of Architecture, Computing & Humanities > Centre for Numerical Modelling & Process Analysis (CNMPA) > Computational Mechanics & Reliability Group (CMRG)
Faculty of Architecture, Computing & Humanities > Department of Mathematical Sciences
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Last Modified: 20 May 2019 16:16
Selected for GREAT 2016: GREAT a
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: GREAT 5
URI: http://gala.gre.ac.uk/id/eprint/13316

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