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The increased demands of today's complex automotive connector designs have led to the development of engineering structural analysis tools which address the performance issues of the connector's snap-finger. In designs where hand calculations were once considered the norm in evaluating snap-finger performance, the analysis tools have evolved into the use of finite element techniques which address the high nonlinearity issues of snap-finger disassembly and terminal pull out strength. The structural analysis approaches developed investigate the connector snap-finger performance in reinforced engineering thermoplastics while incorporating the effects of geometric and material nonlinearity in the results. The techniques developed allow for the evaluation of snap-finger performance of prospective connector designs before expensive tooling and prototyping is initiated, providing the benefits of limited tool rework and decreased product development time.

Gas-assist injection molding is a relatively new process. It is an extension of conventional injection molding and allows molders to make larger parts having projected areas or cross sectional geometries not previously possible using existing equipment. However, controlling the injection of the gas has been a concern. The plastics industry is attempting to establish logical techniques to set up and rationalize processing conditions for the method. Although gas injection equipment permits a number of adjustments, an optimum processing window must be established to provide control and repeatability of the process to mold consistent, acceptable parts. This paper describes a strategy and equipment for rationalizing and accurately controlling gas injection processing conditions that are applicable regardless of the type of molding machine or processing license a molder is using.

A model has been developed and implemented at GE Plastics that predicts a material's color shift when weathered. The material's color shift is due to the summation of color shifts from each individual component. By individually measuring the change in each component's optical coefficients upon weathering and using a multiple light scattering model, one can predict the color shift of a material composed of mixtures of these components. The model has been shown to have a standard deviation of 0.4 to 0.9 when predicting color shifts E*, for PC-polyester copolymers, ABS, and ABS/PC blends using an automotive exterior test, SAE J1885, ASTM D 4674, and ASTM D 4459.

Engineering thermoplastics are increasingly being used in automotive applications; many of whose designs are very complex and can pose unique challenges in manufacturing. To help products reach market faster, with better quality and lower cost, use of predictive engineering methods is becoming increasingly common. The purpose of this paper is to review a specific predictive tool: moldfilling analysis. This paper will outline the technology, what is required to use it properly, what issues the technology is capable of addressing, and what other tools are available for addressing advanced issues.

Automotive engineers and designers are working to develop pillar-trim concepts that will comply with the upper interior head-impact legislation, FMVSS 201U. However, initial development cycles have been long and repetitive. A typical program consists of concept development, tool fabrication, prototype molding, and impact testing. Test results invariably lead to tool revisions, followed by further prototypes, and still more impact testing. The cycle is repeated until satisfactory parts are developed - a process which is long (sometimes in excess of 1 year) and extremely labor intensive (and therefore expensive). Fortunately, the use of finite-element analysis (FEA) can greatly reduce the concept-to-validation time by incorporating much of the prototype and impact evaluations into computer simulations. This paper describes both the correlation and validation of an FEA-based program to physical free-motion head-form testing and the predictive value of this work.