Mixed response surface models and Bayesian analysis of variance components for electrically conductive adhesives. (25th April 2013)

• Record Type: Journal Article
• Authors: Berni, Rossella; Scarano, Valeria Leonarda; Bertocci, Francesco; Catelani, Marcantonio; Borgoni, Riccardo; Deldossi, Laura; Radaelli, Luigi; Zappa, Diego
• Is Part Of: Applied stochastic models in business and industry. Volume 29:Number 4(2013:Jul./Aug.)
• Page Start: 387
• Page End: 398
• Publication Date: 2013-04-25
• Subjects: Stochastic analysis -- Periodicals; Stochastic processes -- Periodicals; Business mathematics -- Periodicals; Finance -- Mathematical models -- Periodicals; Industrial management -- Mathematical models -- Periodicals; 338.00151923
• DOI: 10.1002/asmb.1978
• Languages: English
• ISSNs: 1524-1904

Abstract

<abstract abstract-type="main" id="asmb1978-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p id="asmb1978-para-0001">This paper deals with an analysis of random effects for microelectronic data. More precisely, by considering the technical challenges related to the use of electrically conductive adhesives such as soldering material in electronics, the sources of variabilities related to different electrically conductive adhesive characteristics and working process variables are evaluated. Random effects are involved in a response surface methodology setting, and the results are compared with a Bayesian approach where variance components are estimated through a log‐posterior expressed as the product of the information matrix and restricted maximum likelihood estimates of variance components. Copyright © 2013 John Wiley &amp; Sons, Ltd.</p> </abstract>