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This article presents an approach for comparing alternative repairable systems and calculating the value of information obtained by testing a specified number of such systems. More specifically, an approach is presented to determine the value of information that comes from field testing a specified number of systems in order to appropriately estimate the reliability metric associated with each of the respective repairable systems. Here the reliability of a repairable system will be measured by its failure rate. In support of the decision-making effort, the failure rate is translated into an expected utility based on a utility curve that represents the risk tolerance of the decision-maker. The algorithm calculates the change of the expected value of the decision with the sample size. The change in the value of the decision represents the value of information obtained from testing.

Importance Sampling is a popular method for reliability assessment. Although it is significantly more efficient than standard Monte Carlo simulation if a suitable sampling distribution is used, in many design problems it is too expensive. The authors have previously proposed a method to manage the computational cost in standard Monte Carlo simulation that views design as a choice among alternatives with uncertain reliabilities. Information from simulation has value only if it helps the designer make a better choice among the alternatives. This paper extends their method to Importance Sampling. First, the designer estimates the prior probability density functions of the reliabilities of the alternative designs and calculates the expected utility of the choice of the best design. Subsequently, the designer estimates the likelihood function of the probability of failure by performing an initial simulation with Importance Sampling.

This paper discusses an analytical technique for computing the failure rate of steel springs used in automotive part applications. Preliminary computations may be performed and used to predict spring failure rates quickly at a very early stage of a product development cycle and to establish program reliability impact before commitment. The analytical method is essentially a combination of various existing procedures that are logically sequenced to compute a spring probability of failure under various operational conditions. Fatigue life of a mechanical component can be computed from its S-N curve. For steels, the S-N curve can be approximated by formulae which describe the fatigue life as a function of its endurance limit and its alternating stress. Most springs in service are preloaded and the actual stress fluctuates about a mean level. In order to compute an equivalent alternating stress with zero mean, an analytical method based on the Goodman Diagram is used.

With improvements in casting technology, cast iron can be an alternative to steel in some applications due to its similar strength. One objective of this study was to analyze cast iron data obtained from the literature and evaluate predictive correlations between its tensile, microstructural, and fatigue properties. Reasonably good correlation of tensile strength and yield strength were found with hardness. However, fatigue strength could not be correlated with hardness or tensile properties. Another objective of this study was to evaluate tensile and compressive means stress effects on fatigue behavior of 120-90-02 ductile cast iron experimentally, as well as analytically by using predictive models. Mean stress levels were chosen such that R ratios in load-controlled tests were −7, −3, −1, 0, 1/3, 0.5, and 0.75. Modified Goodman, Smith-Watson-Topper, FKM and the Fatemi-Socie mean stress parameters were used to account for the mean stress effect on fatigue life.

Since 1997, General Motors Body Manufacturing Engineering - Die Engineering Services (BME-DES) has been working jointly with our software vendor to develop and implement a parallel version of stamping simulation software for mass production analysis applications. The evolution of this technology and the insight gained through the implementation of DMP/MPP technology as well as performance benchmarks are discussed in this publication.

Historically, the long development time required to produce a new automobile has meant that the electronics in that vehicle might lag the state-of-the-art by several years. For traditional vehicle electronics, this was certainly an appropriate delay, ensuring through extensive testing and qualification that the quality and reliability of the electronic systems met rigorous standards. However, with the growing consumer-oriented electronics content in today's vehicles, it is becoming more difficult for the automotive manufacturers to meet consumers' expectations with older technology. Couple this with the fast-paced consumer product cycle, typically nine to eighteen and the result is increasing pressure on the vehicle manufacturers from after-market electronics suppliers, who can update their product lines as fast as the component manufacturers can produce new models.

The problem of predicting the quality of weld is critical to manufacturing. A great deal of data is collected under multiple conditions to predict the quality. The data generated at Daimler Chrysler has been used to develop a model based on grammatical evolution. Grammatical Evolution Technique is based on Genetic Algorithms and generates rules from the data which fit the data. This paper describes the development of a software tool that enables the user to choose input variables such as the metal types of top and bottom layers and their thickness, intensity and speed of laser beam, to generate a three dimensional map showing weld quality. A 3D weld quality surface can be generated in response to any of the two input variables picked from the set of defining input parameters. This tool will enable the user to pick the right set of input conditions to get an optimal weld quality. The tool is developed in Matlab with Graphical User Interface for the ease of operation.

This paper presents a computer generated model of a hydraulic circuit that is typically seen in hybrid hydraulic vehicles (HHV's). HHV's have shown considerable potential for increasing fuel economy and decreasing emissions for mid-size and commercial trucks that exhibit urban driving habits. The aim of the present model is to aid in further optimizing the performance of the hybrid powertrain and serve as a baseline for future studies into the noise and vibration (NV) associated with the system. The model simulates the regenerative braking process of a parallel type hybrid hydraulic propulsion system. Regenerative braking captures and stores otherwise lost energy into an accumulator. This stored energy can then later be used to propel the vehicle, thus reducing the vehicle's reliance on a conventional internal combustion engine (ICE). This model will serve as a baseline for future developments and will be expanded and validated experimentally in ensuing research.

The use of regrind acrylonitrile-butadiene-styrene (ABS) for automotive parts and components results in two types of financial savings. The first is the shared monetary savings between General Motors and the molder for the difference in the virgin resin price versus price of the ABS regrind. The second is a societal energy savings seen in the life cycle of virgin ABS versus reground ABS. An added benefit is the preservation of natural resources used to produce virgin ABS.

A complete probabilistic model of uncertainty in probabilistic analysis and design problems is the joint probability distribution of the random variables. Often, it is impractical to estimate this joint probability distribution because the mechanism of the dependence of the variables is not completely understood. This paper proposes modeling dependence by using copulas and demonstrates their representational power. It also compares this representation with a Monte-Carlo simulation using dispersive sampling.

Finite element analysis (FEA) predictions of magnesium beams are compared to load versus displacement test measurements. The beams are made from AM60B die castings, AM30 extrusions and AZ31 sheet. The sheet and die cast beams are built up from two top hat sections joined with toughened epoxy adhesive and structural rivets. LS-DYNA material model MAT_124 predicts the magnesium behavior over a range of strain rates and accommodates different responses in tension and compression. Material test results and FEA experience set the strain to failure limits in the FEA predictions. The boundary conditions in the FEA models closely mimic the loading and constraint conditions in the component testing. Results from quasi-static four-point bend, quasi-static axial compression and high-speed axial compression tests of magnesium beams show the beam's behavior over a range of loadings and test rates. The magnesium beams exhibit significant material cracking and splitting in all the tests.

Magnesium alloy extrusions offer potentially more mass saving compared to magnesium castings. One of the tasks in the United States Automotive Materials Partnership (USAMP) ?Magnesium Front End Research and Development? (MFERD) project is to evaluate magnesium extrusion alloys AM30, AZ31 and AZ61 for automotive body applications. Solid and hollow sections were made by lowcost direct extrusion process. Mechanical properties in tension and compression were tested in extrusion, transverse and 45 degree directions. The tensile properties of the extrusion alloys in the extrusion direction are generally higher than those of conventional die cast alloys. However, significant tension-compression asymmetry and plastic anisotropy need to be understood and captured in the component design.

Magnesium alloys are the lightest structural metal and recently attention has been focused on using them for structural automotive components. Fatigue and durability studies are essential in the design of these load-bearing components. In 2006, a large multinational research effort, Magnesium Front End Research & Development (MFERD), was launched involving researchers from Canada, China and the US. The MFERD project is intended to investigate the applicability of Mg alloys as lightweight materials for automotive body structures. The participating institutions in fatigue and durability studies were the University of Waterloo and Ryerson University from Canada, Institute of Metal Research (IMR) from China, and Mississippi State University, Westmorland, General Motors Corporation, Ford Motor Company and Chrysler Group LLC from the United States.

Fully Flexible Valve Actuation (FFVA) systems provide maximum flexibility to adjust lift profiles of engine intake and exhaust valves. A research grade electro-hydraulic servo valve based FFVA system was designed to be used with an engine in a test cell to precisely follow desired lift profiles. Repetitive control was chosen as the control strategy. Crank angle instead of time is used to trigger execution to ensure repeatability. A single control is used for different engine speeds even though the period for one revolution changes with engine speeds. The paper also discusses lift profile extension, instantaneous lift profile switching capability and built-in safety features.

Casting, machining and structural simulations were completed on a V8 engine block made in Compacted Graphite Iron (CGI) for use in a racing application. The casting and machining simulations generated maps of predicted tensile strength and residual stress in the block. These strength and stress maps were exported to a finite element structural model of the machined part. Assembly and operating loads were applied, and stresses due to these loads were determined. High cycle fatigue analysis was completed, and three sets of safety factors were calculated using the following conditions: uniform properties and no residual stress, predicted properties and no residual stress, and predicted properties plus residual stress.

The Auto/Steel Partnership established the Light Truck Frame Project Group in 1996 with two objectives: (a) to develop materials, design and fabrication knowledge that would enable the frames on North American OEM (original equipment manufacturer) light trucks to be reduced in weight, and (b) to improve corrosion resistance of frames on these vehicles, thereby allowing a reduction in the thickness of the components and a reduction in frame weight. To address the issues relating to corrosion, a subgroup of the Light Truck Frame Project Group was formed. The group comprised representatives from the North American automotive companies, test laboratories, frame manufacturers, and steel producers. As part of a comprehensive test program, the Corrosion Subgroup has completed tests on frame coatings. Using coated panels of a low carbon hot rolled and pickled steel sheet and two types of accelerated cyclic corrosion tests, seven frame coatings were tested for corrosion performance.

This report summarizes the methodology used in automotive industry for virtual evaluation of vehicle structural integrity under abusive load cases. In particular, the development of a nonlinear finite element (FE) centric approach is covered that is based on the functions implemented in ABAQUS (by ABAQUS Inc.). An overview is also given for comparative study of the ABAQUS capability with the existing ADAMS (MSC Software) based methods.

The overall vision of this project was to develop a new technology that will be an enabler to reduce design and development time of HVAC systems by an order of magnitude. The objective initially was to develop a parametric model of an automotive HVAC Windshield Defrost Duct coupled to a passenger compartment. It can be used early on in the design cycle for conducting coarse packaging studies by quickly exploring “what-if” design alternatives. In addition to the packaging studies, performance of these design scenarios can be quickly studied by undertaking CFD simulation and analyzing flow distribution and windshield melting patterns. The validated geometry and CFD models can also be used as knowledge building tools to create knowledge data warehouses or repositories for precious lessons learned.

In order to engineer Squeak & Rattle (S&R) free vehicles it is essential to develop an objective measurement method to compare and correlate with customer satisfaction and subjective S&R assessments. Three methods for exciting S&Rs -type surfaces. Excitation methods evaluated were road tests over S&R surfaces, road simulators, and direct body excitation (DBE). The principle of DBE involves using electromagnetic shakers to induce controlled, road-measured vibration into the body, bypassing the tire patch and suspension. DBE is a promising technology for making objective measurements because it is extremely quiet (test equipment noise does not mask S&Rs), while meeting other project goals. While DBE is limited in exposing S&Rs caused by body twist and suspension noises, advantages include higher frequency energy owing to electro-dynamic shakers, continuous random excitation, lower capital cost, mobility, and safety.

A gasoline direct injection fuel spray was observed using a fired, optical access, square cross-section single cylinder research engine and high-speed video imaging. Spray interaction with the piston is described qualitatively, and the results are compared with Computational Fluid Dynamics (CFD) simulation results using KIVA-3V version 2. CFD simulations predicted that within the operating window for stratified charge operation, between 1% and 4% of the injected fuel would remain on the piston as a liquid film, dependent primarily on piston temperature. The experimental results support the CFD simulations qualitatively, but the amount of fuel film remaining on the piston appears to be under-predicted. High-speed video footage shows a vigorous spray impingement on the piston crown, resulting in vapor production.