Table gives the list of components which will be modeled

Table 1 gives the list of components which will be modeled. Transient Voltage Suppressor (TVS) as well as passive elements will be also modeled. For each component, we will choose the EMC (emission and immunity) and transient immunity measurement method adapted to extract the component model. A complete ELECIS demonstrator model will be established in white box by the association of different active, passive components models as well as the PCB tracks. EMC (emission and immunity) and transient\'s immunity normative set-up models will be established which will require the creation of cable, antennas, injection probe pulse generator, and ESD gun models. Fig. 9 shows an example of BCI (Bulk Current Injection) set-up modeling as presented in the paper [7]. This modeling allows to calculate the equivalent DPI (Direct Power Injection) level obtain at component level during a BCI test.
Characterization/modeling of package on substrate mechanical assembly Furthermore, during the manufacturing process, the quality of the soldered joints can fluctuate. IPCA610 defines certain rules to accept or reject the imperfections. However, it Reutericyclin mass is not possible to quantify the influence of imperfections on the assembly lifetime during thermo-mechanical stresses. The objective of this work is therefore to determine the influence of soldered joints geometry illustrated by Fig. 10 (form and imperfection) on the reliability of microelectronic assemblies. The joint use of simulations and a degradation law allows studying the influence of the dispersion of a technological parameter on the distribution of the service life of an assembly [8]. The value of calculable parameters, such as the accumulated maximum deformation and the maximum stress or strain energy, is directly related to the dimensions and the geometry of the structure and also on material characteristics and the simulated load conditions. These parameters can themselves be dependent on fluctuations in the manufacturing process and of changes in the conditions of the environment of Assembly (mission profile). Therefore, they must be considered as random variables as soon as we want to evaluate the distribution of the life of the Assembly. To consider the influence of the variation of one of these measurable parameters on the distribution of the lifetime of the connection, we can start by studying its influence on the variation of one of the parameters calculated by finite elements. Studied assemblies, provided by Continental Automotive France, behave 0.5mm pitch BGA and QFN Packages. They must be characterized after the manufacturing phase to determine the most fluctuating geometric parameters: heights of joints, the presence and size of voids, etc. From these measurements on real soldered joints, e.g., by 3D Rx measuring, relevant parameters must be identified, and then their dispersion modeled. A set of numerical simulations by finite element will be undertaken to assess the impact of dispersal on the thermomechanical constraints of Assembly.
Conclusion
Acknowledgments This project is sponsored by Airbus Operations, Airbus Group Innovations, Continental Automotive France, Hirex Engineering, Labinal Power Systems, Nexio, Thales Alenia Space France, Thales Avionics and French National Agency for Research (ANR). The authors thank Serma Technologies for GaN transistor construction analyses.
Introduction Component-based software development usually involves assembling and developing reusable components (Crnkovic, 2001). In this study a component is referred to as an asset, which when incorporated into a system adds value (functional and/or non-functional) to the end customer. Hence assembling or developing operating systems components or databases components are out of the scope of this study. Each component can be obtained from a different source, we refer to the sources as component origins in this study. Four of the widely used component origins are considered in this study as follows: