Predicting optimal process conditions for flip-chip aassembly using copper column bumped dies

Recently, research has been carried out to test a novel bumping method which omits the under bump metallurgy (UBM) forming process by bonding copper columns directly onto the Al pads of the silicon dies. This bumping method could be adopted to simplify the flip chip assembly process, increase the productivity and achieve a higher I/O count. Computer modelling methods are used to predict the shape of solder joints and response of the flip chip to thermal cyclic loading. The accumulated plastic strain energy at the comer solder joints is used as the damage indicator. Models with a range of design parameters have been compared for their reliability. The ranking of the relative importance of these parameters is given. Results from these analyses are being used by our industrial and academic partners to identify optimal design conditions.

Computer modelling of the reliability of flip chips with metal column bumping

Recently, research has been carried out to test a novel bumping method which omits the under bump metallurgy forming process by bonding copper columns directly onto the Al pads of the silicon dies. This bumping method could be adopted to simplify the flip chip manufacturing process, increase the productivity and achieve a higher I/O count. This paper describes an investigation of the solder joint reliability of flip-chips based on this new bumping process. Computer modelling methods are used to predict the shape of solder joints and response of flip chips to thermal cyclic loading. The accumulated plastic strain energy at the comer solder joints is used as the damage indicator. Models with a range of design parameters have been compared for their reliability. The parameters that have been investigated are the copper column height, radius and solder volume. The ranking of the relative importance of these parameters is given. For most of the results presented in the paper, the solder material has been assumed to be the lead-free 96.5Sn3.5Ag alloy but some results for 60Sn40Pb solder joints have also been presented.

Predicting the relationship between reliability and geometric parameters of cu column bumped flip-chips

Cu column bumping is a novel flip chip packaging technique that allows Cu columns to be bonded directly with the dies. It has eliminated the under-bump-metallurgy (UBM) fonnation step of the traditional flip chip manufacturing process. This bumping technique has the potential benefits of simplifying the flip chip manufacturing process, increasing productivity and the UO counts. In this paper, a study of reliability of Cu column bumped flip chips will be presented. Computer modelling methods have been used to predict the shape of solder joints and the response of flip chips to cyclic thermal-mechanical loading. The accumulated plastic strain energy at the corner solder joints has been used as an indicator of the solder joint reliability. Models with a wide range of design parameters have been compared for their reliability. The design parameters that have been investigated are the copper column height and radius, PCB pad radius, solder volume and Cu column wetting height. The relative importance ranking of these parameters has been obtained. The Lead-free solder material 96.5Sn3.5Ag has been used in this modelling work.

Bivariate distribution modeling with tree diameter and height data

The Logit-Logistic (LL), Johnson's SB, and the Beta (GBD) are flexible four-parameter probability distribution models in terms of the (skewness-kurtosis) region covered, and each has been used for modeling tree diameter distributions in forest stands. This article compares bivariate forms of these models in terms of their adequacy in representing empirical diameter-height distributions from 102 sample plots. Four bivariate models are compared: SBB, the natural, well-known, and much-used bivariate generalization of SB; the bivariate distributions with LL, SB, and Beta as marginals, constructed using Plackett's method (LL-2P, etc.). All models are fitted using maximum likelihood, and their goodness-of-fits are compared using minus log-likelihood (equivalent to Akaike's Information Criterion, the AIC). The performance ranking in this case study was SBB, LL-2P, GBD-2P, and SB-2P