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The current study shows important results obtained by a new technique of residual stress virtual evaluation in automotive components for improving the development and quality of new products, aiming the structural performance, mass and cost reductions. The approaching those virtual results were adjusted by metallurgic data obtained in metallography, mechanical and chemical analysis. As part of this proposal, an automotive aluminum wheel belong to current production was evaluated in accordance with data acquired in the wheel manufacturing process. It was taking in account the real information of casting process parameters and the metallurgic information obtained in laboratorial tests. In this work, the results show that product residual stresses shall be considerate and evaluated during design phases as improving proposal, new technical concerns and quality improving.

Development of an Electrical Power Steering (EPS) system for Emergent Markets, with emphasis on improved fuel economy and cost advantages to the customer. The EPS for Emergent Markets provides high steering wheel assistance on parking maneuvers and appropriate assistance on driving conditions similar to conventional EPS systems. The assistance levels decreases while vehicle speed increases providing better steering feel at high speed conditions (highway tracks). It also provides good tuning capability balanced with piece cost. In addition, this EPS enables an aftermarket bolt-on system for non-assisted steering vehicles (i.e., manual steering vehicles).

The growing need to avoid failures in vehicle components have become the methods of quality control of manufacturing processes more efficient and accurate, especially in safety components like automotive wheels. The aim of this work is examines the efficiency of aluminum-silicon specifications related to wheel quality for avoiding the poor results obtained in impact and fatigue tests as result of improper settings in the chemical composition and manufacture process. It is evaluated mainly the content of magnesium in aluminum alloys and certified the correct degree of silicon modification in the microstructure on the performance of these wheels. The test results indicate that even with the chemical composition parameters specified by the standard, the technical validation of the product may not be adequate.

In the middle of the global competition, inside the automotive sector, the perceived quality of costumers, related to the beauty and harmony of the outer skin surfaces of motor vehicles, has become one of the main determinant factors in the purchase process decision. In general, the initial perceived quality of a car is determined by an appealing design of its body, the color and gloss of its paint, and also the manufacturing and assembly accuracy of the skin panels. The appealing design makes the skin panel even more complex and hard to produce with current metal forming technologies and the results are often small distortions on the outer surfaces about tens of microns and most of the times paint does not cover such imperfections. Despite the technological advances along the years, surface quality inspection was still being performed by manual and subjective evaluation by experts.

This paper proposes a methodology for automotive manufacturing lines scheduling. This methodology is based on generalized stochastic Petri Nets and Markov decision processes with imprecise probabilities. The usual generalized stochastic Petri Nets is extended by allowing imprecision about probabilities to be explicitly represented and by human task time graph of different products to be attached. Once the system is modeled using this tool and its extensions, we translate the resulting models into Markov decision processes with imprecise probabilities, in order to compute optimal policies that will result in the line scheduling. This paper introduces an algorithm that performs this translation.

Acoustics, in a broad sense, is an essential product attribute in the automotive industry, therefore, it is relevant to study and compare theoretical and numerical predictions to experimental acoustic measurements, key elements of many acoustic development processes. The numerical methods used in the industry for acoustic predictions are widely used for exhaust system optimization. However, the numerical and theoretical predictions very often differ from experimental results, due to modeling simplifications, temperature variations (which have high influence on speed of sound), manufacturing variations in prototype parts among others. This article aims to demonstrate the relevant steps for acoustics development applied in automotive exhaust systems and present a comparative study between experimental tests and computer simulations results for each process. The exhaust system chosen for this development was intended for a popular car 4-cylinder 1.0-liter engine.

This paper makes an analysis of problems encountered in assembling components from automotive vehicles. It shows wheel and tires assembling cases of an automaker that applies lean manufacturing concepts in the production process. This study not only makes the analysis from the best way to apply the methodology to seek for the root cause, but also uses methodology to identify containment measures, defining robust solutions capable of preventing the incidence of similar problems. This methodology can be applied to solving problems of any production process, even outside of the automotive industry

This paper explores the method of modeling and validation the computational tools able to accurately replicate the dynamic behavior of a Formula SAE vehicle. Based on limitations in conducting physical tests, it is possible to mathematically predict the forces and momentum generated on the steering column of the vehicle, minimizing effort and improving driver comfort even before the component physically manufactured. The results in permanent state due technical instrumentations were used in the physical vehicles and compared with other proposals (skid Pad test). As the software simulating the same path, it was possible to adopt values of speed and wheel steering, allowing compare the dynamics of the vehicle, through the signals from other sensors installed in the data acquisition system, validating the behavior of the models presented in permanent state. Other aspects were studied to understand vehicle behavior concerning lateral stability and steering behavior.