An integrated approach to flow, thermal and mechanical modeling of electronics devices

The future success of many electronics companies will depend to a large extent on their ability to initiate techniques that bring schedules, performance, tests, support, production, life-cycle-costs, reliability prediction and quality control into the earliest stages of the product creation process. Earlier papers have discussed the benefits of an integrated analysis environment for system-level thermal, stress and EMC prediction. This paper focuses on developments made to the stress analysis module and presents results obtained for an SMT resistor. Lifetime predictions are made using the Coffin-Manson equation. Comparison with the creep strain energy based models of Darveaux (1997) shows the shear strain based method to underestimate the solder joint life. Conclusions are also made about the capabilities of both approaches to predict the qualitative and quantitative impact of design changes.

Exploiting virtual prototyping for reliability assessment

Products manufactured by the electronics sector are having a major impact in telecommunications, transportation space applications, biomedical applications, consumer products, intelligent hand held devices, and of course,the computer. Demands from end-users in terms of greater product functionality, adoption of environmentally friendly materials, and further miniaturization continually pose several challenges to electronics companies. In the context of electronic product design and manufacture, virtual prototying software tools are allowing companies to dramatically reduce the number of phsysical prototypes and design iterations required in product development and hence reduce costs and time to market. This paper details of the trends in these technolgies and provides an example of their use for flip-chip assembly technology.

Financing of SME's: an asset side story

The main sources of financing for small and medium sized enterprises (SMEs) are equity (internally generated cash), trade credit paid on time, long and short term bank credits, delayed payment on trade credit and other debt. The marginal costs of each financing instrument are driven by asymmetric information (cost of gathering and analysing information) and transactions costs associated with non-payment (costs of collecting and selling collateral). According to the Pecking Order Theory, firms will choose the cheapest source in terms of cost. In the case of the static trade-off theory, firms choose finance so that the marginal costs across financing sources are all equal, thus an additional Euro of financing is obtained from all the sources whereas under the Pecking Order Theory the source is determined by how far down the Pecking Order the firm is presently located. In this paper, we argue that both of these theories miss the point that the marginal costs are dependent of the use of the funds, and the asset side of the balance sheet primarily determines the financing source for an additional Euro. An empirical analysis on a unique dataset of Portuguese SME's confirms that the composition of the asset side of the balance sheet has an impact of the type of financing used and the Pecking Order Theory and the traditional Static Trade-off theory are rejected.

Dynamic evolution in information sharing networks

This study examines the roll-out of a collaborative information repository or 'knowledge-base' in a medium-sized UK professional services firm over a six year period. Data from usage logs provides the basis for analysis of the dynamic evolution of social networks around the depository during this time. The adoption pattern follows an 's-curve' and usage exhibits something of a power law distribution, both attributable to network effects and network opposition is associated with organisational performance on a number of indicators. But periodicity in usage is evident and the usage distribution displays an exponential cut-off. Fourier analysis provides some evidence of mathematical complexity in the periodicity. Some implications of complex patterns in social network data for research and management are discussed.