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Warranty forecasting of repairable systems is very important for manufacturers of mass produced systems. It is desired to predict the Expected Number of Failures (ENF) after a censoring time using collected failure data before the censoring time. Moreover, systems may be produced with a defective component resulting in extensive warranty costs even after the defective component is detected and replaced with a new design. In this paper, we present a forecasting method to predict the ENF of a repairable system using observed data which is used to calibrate a Generalized Renewal Processes (GRP) model. Manufacturing of products may exhibit different production patterns with different failure statistics through time. For example, vehicles produced in different months may have different failure intensities because of supply chain differences or different skills of production workers, for example.

This study is a joint development project between Chrysler Corporation and CFD Research Corporation. The objective of this investigation was to develop a 3D computational flow and heat transfer model for a vehicle windshield de-icing process. The windshield clearing process is a 3D transient, multi-medium, multi-phase heat exchange phenomenon in connection with the air flow distribution in the passenger compartment. The transient windshield de-icing analysis employed conjugate heat transfer methodology and enthalpy method to simulate the velocity distribution near the windshield inside surface, and the time progression of ice-melting pattern on the windshield outside surface. The comparison between the computed results and measured data showed very reasonable agreement, which demonstrated that the developed analysis tool is capable of simulating the vehicle cold room de-icing tests.

We have recently obtained experimental data and used them to develop computational models to quantify occupant impact responses and injury risks for military vehicles during frontal crashes. The number of experimental tests and model runs are however, relatively small due to their high cost. While this is true across the auto industry, it is particularly critical for the Army and other government agencies operating under tight budget constraints. In this study we investigate through statistical simulations how the injury risk varies if a large number of experimental tests were conducted. We show that the injury risk distribution is skewed to the right implying that, although most physical tests result in a small injury risk, there are occasional physical tests for which the injury risk is extremely large. We compute the probabilities of such events and use them to identify optimum design conditions to minimize such probabilities.

The flow field contained within ten planes inside a cylinder of a 3.5 liter, 24-valve, V-6 engine was mapped using a three-dimensional Laser Doppler Velocimetry (3-D LDV) system. A total of 1,548 LDV measurement locations were used to construct the time history of the in-cylinder flow fields during the intake and compression strokes. The measurements began during the intake stroke at a crank angle of 60° ATDC and continued until approximately 280° ATDC. The ensemble averaged LDV measurements allowed for a quantitative analysis of the dynamic in-cylinder flow process in terms of tumble and swirl motions. Both of these quantities were calculated at every 1.8 crank degrees during the described measurement interval. Tumble calculations were performed about axes in multiple planes in both the Cartesian directions perpendicular to the plane of the piston top. Swirl calculations were also accomplished in multiple planes that lie parallel to the plane of the piston top.

This paper discusses simplified lumped parameter thermal modeling of power train components. In particular, it discusses the tradeoff between model complexity and the ability to correlate the predicted temperatures and flow rates with measured data. The benefits and problems associated with using a three lumped mass model are explained and the value of this simpler model is promoted. The process for correlation and optimization using modern software tools is explained. Examples of models for engines and transmissions are illustrated along with their predictive abilities over typical driving cycles.

Reliability is an important engineering requirement for consistently delivering acceptable product performance through time. As time progresses, the product may fail due to time-dependent operating conditions and material properties, component degradation, etc. The reliability degradation with time may increase the lifecycle cost due to potential warranty costs, repairs and loss of market share. Reliability is the probability that the system will perform its intended function successfully for a specified time interval. In this work, we consider the first-passage reliability which accounts for the first time failure of non-repairable systems. Methods are available in the literature, which provide an upper bound to the true reliability which may overestimate the true value considerably. Monte-Carlo simulations are accurate but computationally expensive.

Reliability is an important engineering requirement for consistently delivering acceptable product performance through time. As time progresses, the product may fail due to time-dependent operating conditions and material properties, component degradation, etc. The reliability degradation with time may increase the lifecycle cost due to potential warranty costs, repairs and loss of market share. Reliability is the probability that the system will perform its intended function successfully for a specified time interval. In this work, we consider the first-passage reliability which accounts for the first time failure of non-repairable systems. Methods are available in the literature, which provide an upper bound to the true reliability which may overestimate the true value considerably. This paper proposes a methodology to calculate the cumulative probability of failure (probability of first passage or upcrossing) of a dynamic system, driven by an ergodic input random process.

PLYMOUTH'S new V-8 engine has a specific output of 0.65 bhp/cu in. and 145-psi bmep — obtained through a combination of high thermal, volumetric, and mechanical efficiencies. Good design, the author points out, has achieved this high output despite the dual-venturi carburetor and the 7.6/1 compression ratio, selected for satisfactory operation on regular-grade fuels. The engine has a bore and stroke of 3.563 × 3¼, weighs 568 lb without flywheel, is 29⅜ in. long, and is designed for optimum response to future compression ratio increases. (A report of oral discussion following presentation of this paper appears on p. 220, following “The New Packard V-8 Engine,” by W. E. Schwieder.)

The SAE Recommended Practice J963 “Anthropomorphic Test Device for Dynamic Testing” describes a standard 50th percentile adult male anthropomorphic test dummy. For nearly three years the Crash Test Dummy Task Force worked with the limited data available in selecting values for the body dimensions and ranges of motion. The data for specifying the values of mass distribution were developed experimentally as was a test procedure for determining the dynamic spring rate of the thorax.

A selection of commercially available chromium and chromium-free post phosphate rinses along with a deionized water rinse were evaluated over several zinc and zinc-alloy coated sheet steels. The test specimens were pretreated and electrocoated on-line in an automotive assembly plant. The effect of the rinse treatments on the cosmetic corrosion performance of the substrates, after 5 years of exposure in an outdoor scab corrosion test was determined. After this exposure none of the rinse treatments had performed better than deionized water rinse on zinc and zinc-iron coated sheet. The zinc-nickel coating showed improved scribe creepage when treated with the Cr+6/Cr+3 rinse. Data is provided comparing the concentration of the treatments used vs scribe creepage and chipping corrosion paint loss.

Most of the current fuel supply specifications, including the key parameters in the transient fuel control strategies, are experimentally determined since the complexity of multiphase fuel flow behavior inside the intake manifold is still not quantitatively understood. Optimizing these specifications, especially the parameters in transient fueling systems, is a key issue in improving fuel efficiency and reducing exhaust emissions. In this paper, a model of fuel spray, wall-film flow and wall-film vaporization has been developed to gain a better understanding of the multiphase fuel-flow behavior within the intake manifold which may help to determine the fuel supply specifications in a multi-point injection system.

A highly competitive market and increased emphasis on quality have gear designers searching for additional tools to produce accurate gearsets in a condensed timeframe. To meet this challenge, a Graphics Engineering method has been developed to enhance traditional gear design techniques. Graphics Engineering links interactive graphics, finite element analysis and solid modeling into a graphics/analysis development package. Starting with gear and cutter data derived by conventional techniques, it provides cutter paths and involute profiles for geometry, strength, and physical property analysis. The comprehensive data obtained through Graphics Engineering provides a powerful tool for the gear designer to increase gearset accuracy and reduce design iterations.

TFC/IW, total fuel consumption divided by inertia (test) weight is a useful concept in analyzing the total or composite fuel economy generated in thousands of tests using the carbon balance technique in EPA Federal Test Procedure and Highway Driving Cycle. TFC/IW is a measure of drive train efficiency that requires no additional complicating assumptions. It is applicable to one test or a fleet representing many tests.

In this article we present an approach to identify the system topology using simulation for reliability calculations. The system topology provides how all components in a system are functionally connected. Most reliability engineering literature assumes that either the system topology is known and therefore all failure modes can be deduced or if the system topology is not known we are only interested in identifying the dominant failure modes. The authors contend that we should try to extract as much information about the system topology from failure or success information of a system as possible. This will not only identify the dominant failure modes but will also provide an understanding of how the components are functionally connected, allowing for more complicated analyses, if needed. We use an evolutionary approach where system topologies are generated at random and then tested against failure or success data. The topologies evolve based on how consistent they are with test data.

Reaching a system level reliability target is an inverse problem. Component level reliabilities are determined for a required system level reliability. Because this inverse problem does not have a unique solution, one approach is to tradeoff system reliability with cost and to allow the designer to select a design with a target system reliability, using his/her preferences. In this case, the component reliabilities are readily available from the calculation of the reliability-cost tradeoff. To arrive at the set of solutions to be traded off, one encounters two problems. First, the system reliability calculation is based on repeated system simulations where each system state, indicating which components work and which have failed, is tested to determine if it causes system failure, and second, the task of eliciting and encoding the decision maker's preferences is extremely difficult because of uncertainty in modeling the decision maker's preferences.

The object of this paper is to present an overview of the procedure leading to the selection of suspension system pivot points, show how to resolve terrain and maneuver loads at the tire contact patch to the vehicles' structure, illustrate the modeling technique used for stress analysis of suspension system components, and illustrate a few examples of suspension system models used to aid in the solution of ride and handling problems.

An automotive cockpit module is a complex assembly, which consists of components and sub-systems. The critical systems in the cockpit module are the instrument panel (IP), the floor console, and door trim assemblies, which consist of many plastic trims. Stiffness is one of the most important parameters for the plastic trims' design, and it should be optimum to meet all the three functional requirements of safety, vibration and durability. This paper presents how the CAE application and various other techniques are used efficiently to predict the stiffness, and the strength of automotive cockpit systems, which will reduce the product development cycle time and cost. The implicit solver is used for the most of the stiffness analysis, and the explicit techniques are used in highly non-linear situations. This paper also shows the correlations of the CAE results and the physical test results, which will give more confidence in product design and reduce the cost of prototype testing.

This paper presents a method of accounting for sample variability and sample size in establishing the acceptable bogey levels. The technique makes use of the statistical tolerance theory which accounts for the variability of the sample mean and standard deviation by determining a K-factor adjusted for sample size. The result is a tolerance that is reasonably assumed to cover a specified fraction of the population of parts. The technique, although not as simple as a fixed bogey, does discriminate between designs with different levels of energy management robustness.

Although numerical simulation techniques for sheet metal forming become increasingly maturing in recent years, prediction of springback remains a topic of current investigation. The main point of this paper is to illustrate the effectiveness of a modelling approach where static implicit schemes are used for the prediction of springback regardless whether a static implicit or dynamic explicit scheme is used in the forming simulation. The approach is demonstrated by revisiting the 2-D draw bending of NUMISHEET'93 and numerical results on two real world stampings.

A running loss test procedure has been developed which integrates a point-source collection method to measure fuel evaporative running loss from vehicles during their operation on the chassis dynamometer. The point-source method is part of a complete running loss test procedure which employs the combination of site-specific collection devices on the vehicle, and a sampling pump with sampling lines. Fugitive fuel vapor is drawn into these collectors which have been matched to characteristics of the vehicle and the test cell. The composite vapor sample is routed to a collection bag through an adaptation of the ordinary constant volume dilution system typically used for vehicle exhaust gas sampling. Analysis of the contents of such bags provides an accurate measure of the mass and species of running loss collected during each of three LA-4* driving cycles. Other running loss sampling methods were considered by the Auto-Oil Air Quality Improvement Research Program (AQIRP or Program).