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The rapid growth of electronic feature content within the vehicle continues to challenge the automotive industry. Customers want cutting edge consumer electronics features in a vehicle before the features are obsolete. However, automotive manufacturers continue to struggle with introducing new features into vehicles before they become obsolete to the customer. The ability for automotive manufacturers to seamlessly upgrade existing products with new and improved products continues to plague the automotive industry. Vehicles traditionally take 4 plus years to design and manufacture. Automotive manufacturers need to plan consumer electronics features early, but not actually integrate those into the vehicle until late in the design cycle, possibly on the production line. This would help facilitate providing the most recent features.

A common hurdle to enterprise-wide implementation of Six Sigma projects is the need to prepare employees so they are able to use statistical tools and graphical analysis techniques. Six Sigma deployment plans are replete with classes, seminars and coaching sessions aimed at the use and application of statistical procedures. Master Black Belts, Black Belts and external consultants are engaged in developing tutorial aids, analysis macros, and automated analysis routines so employees do not have to know too much to get the job done. A long term solution to this problem is to work with education providers and help them understand the industry's need for a better prepared work force. People who graduate from engineering, business and management programs need to be equipped with work-ready skills so they can make immediate contributions in the workplace.

The concept of full vehicle simulation has been embraced by the automobile industry as it is an indispensable tool for analyzing vehicles. Vehicle loads traditionally obtained by road load data acquisition such as wheel forces are typically not invariant as they depend on the vehicle that was used for the measurement. Alternatively, virtual road load data acquisition approach has been adopted in industry to derive invariant loads. Analytical loads prior to building hardware prototypes can shorten development cycles and save costs associated with data acquisition. The approach described herein estimate realistic component load histories with sufficient accuracy and reasonable effort using full vehicle simulations. In this study, a multi-body dynamic model of the vehicle was built and simulated over digitized road using ADAMS software, and output responses were correlated to a physical vehicle that was driven on the same road.

The vehicle environment is known to be a demanding context for efficiently displaying information to the driver. Research in typography reveals some factors that influence reading performance measures, but there is limited research on the influence of typographic design elements in a driver-vehicle interface on user performance with a simulated driver task. Participants in these studies completed a set of vehicle infotainment tasks that involved a text-based item search in a custom-designed interface that employed a family of Helvetica Neue fonts, in a static environment and a driving simulator environment. Analysis of the data from the two studies reveals a modest but statistically significant effect of font on certain driving-related task performance measures. In both studies, fonts with intermediate values of character width and line thickness were associated with the best performance on a simulated driving task.

This paper describes a comprehensive methodology for the simulation of vehicle body panel buckling in an electrophoretic coat (electro-coat or e-coat) and/or paint oven environment. The simulation couples computational heat transfer analysis and structural analysis. Heat transfer analysis is used to predict temperature distribution throughout a vehicle body in curing ovens. The vehicle body temperature profile from the heat transfer analysis is applied as an input for a structural analysis to predict buckling. This study is focused on the radiant section of the curing ovens. The radiant section of the oven has the largest temperature gradients within the body structure. This methodology couples a fully transient thermal analysis to simulate the structure through the electro-coat and paint curing environments with a structural, buckling analysis.