The Development of Cost and Size Analysis for the Assessment of Embedded Passives in Printed Circuit Boards

Passive components are electrical components that do not provide amplification or gain. The primary functions of passive components are to manage buses, bias, decouple power and ground (bypass), filter, tune, convert, sense and protect. In 2001, passive devices accounted for 91% of all components, 41% of board area and 92% of all solder joints in an electronic system but only 2.6% were integrated in some fashion. The integrated circuit industry is achieving faster speeds by shrinking technology. This dictates that the passive solution must also shrink. In addition, the need to drive out every cent of costs, improve product reliability and the high passive to active ratios have motivated system manufacturers to consider higher levels of passive integration. These factors have increased interest in embedded passives. This research examines the size and cost tradeoffs associated with the use of embedded passive technology for resistor and capacitors, and creates the models and methodology necessary to determine the coupled size/cost impact of embedding passives. It also examines the effects of embedding resistors on profit margin and throughput. A version of the model for performing tradeoff analyses is delivered via the CALCE Consortium and used by board manufacturers and system designers at this time. The models developed have also been used to determine the optimal number of passive devices to embed in a given system by implementing them within a Multi-Population Genetic Algorithm (MPGA). Boards from several different applications are analyzed to demonstrate the applicability of the models and the optimization approach. The effect of board size on the optimum embedded passive solution was studied and an assessment of whether better system solutions can be found was performed. The analysis has shown that the system size limitation when embedded passives are used is not only dependent on the quantity, type, and electrical properties of the embeddable components, but is, in fact, more dependent on layout constraints associated with the placement of the non-embeddable parts. Studies indicate that the higher the embeddable passive density, the greater the probability that placement can be improved when passives are embedded

Autonomous Evolutionary Art

Eiben, A.E. [Promotor

A study of diversity in multipopulation genetic programming

In the past few years, we have done a systematic experimental investigation of the behavior of multipopulation GP [2] and we have empirically observed that distributing the individuals among several loosely connected islands allows not only to save computation time, due to the fact that the system runs on multiple machines, but also to find better solution quality. These results have often been attributed to better diversity maintenance due to the periodic migration of groups of “good ” individuals among the subpopulations. We also believe that this might be the case and we study the evolution of diversity in multi-island GP. All the diversity measures that we use in this paper are based on the concept of entropy of a population P, defined as H(P)= − ∑ N j=1 Fj log(Fj).Ifweare considering phenotypic diversity, we define Fj as the fraction nj/N of individuals in P having a certain fitness j, where N is the total number of fitness values in P. In this case, the entropy measure will be indicated as Hp(P) or simply Hp. To define genotypic diversity, we use two different techniques. The first one consists in partitioning individuals in such a way that only identical individuals belong to the same group. In thi