Logic circuit exhibits optimum performance

Performance of circuits are compared to determine the optimum circuit configuration for implementation into microelectronic functions. Comparison is made in terms of power drain, propagation time, and component variations with temperature and load

Multiple imputation for continuous variables using a Bayesian principal component analysis

We propose a multiple imputation method based on principal component analysis (PCA) to deal with incomplete continuous data. To reflect the uncertainty of the parameters from one imputation to the next, we use a Bayesian treatment of the PCA model. Using a simulation study and real data sets, the method is compared to two classical approaches: multiple imputation based on joint modelling and on fully conditional modelling. Contrary to the others, the proposed method can be easily used on data sets where the number of individuals is less than the number of variables and when the variables are highly correlated. In addition, it provides unbiased point estimates of quantities of interest, such as an expectation, a regression coefficient or a correlation coefficient, with a smaller mean squared error. Furthermore, the widths of the confidence intervals built for the quantities of interest are often smaller whilst ensuring a valid coverage.Comment: 16 page

Consideration of residual stress and geometry during heat treatment to decrease shaft bending

In automotive industry, heat treatment of components is implicitly related to distortion. This phenomenon is particularly obvious in the case of gearbox parts because of their typical geometry and precise requirements. Even if distortion can be anticipated to an extent by experience, it remains complex to comprehend. Scientific literature and industrial experience show that the whole manufacturing process chain has an influence on final heat treatment distortions. This paper presents an approach to estimate the influence of some factors on the distortion, based on the idea of a distortion potential taking into account not only geometry but also the manufacturing process history. Then the idea is developed through experiments on an industrial manufacturing process to understand the impact of residual stress due to machining on shaft bending and teeth distortion during heat treatment. Instead of being measured, residual stress is being neutralized. By comparing lots between each other, connections between gear teeth geometry and manufacturing steps before heat treatment are obtained. As a consequence, geometrical nonconformities roots can be determined more easily thanks to this diagnosis tool, and corrective actions can be applied. Secondly, the influence of product geometry on bending is experimentally considered. Moreover, metallurgical observations enable to explain the influence of workpieces geometry on shaft bending. Thanks to the obtained results, process and product recommendations to decrease shafts bending are proposed

FactoMineR: An R Package for Multivariate Analysis

In this article, we present FactoMineR an R package dedicated to multivariate data analysis. The main features of this package is the possibility to take into account different types of variables (quantitative or categorical), different types of structure on the data (a partition on the variables, a hierarchy on the variables, a partition on the individuals) and finally supplementary information (supplementary individuals and variables). Moreover, the dimensions issued from the different exploratory data analyses can be automatically described by quantitative and/or categorical variables. Numerous graphics are also available with various options. Finally, a graphical user interface is implemented within the Rcmdr environment in order to propose an user friendly package.