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In the developement process, the engineer is required to design, validate and deliver the components for manufacturing, in an as short as possible lead time. For that, the engineer may use some available tools to save not only time, but also cost. This work presents a zero prototype approach applyied to a plastic component, whose main accomplishment was the decreasing of lead time development due to the intensive use of virtual tools (CAD/CAE). As a result, the product was delivered in a short time, with no need of building physical prototypes, thus reducing development cost.

Recent applied mathematics research on the properties of the invertible shift-invariant discrete wavelet transform has produced new ways to visualize, separate, and synthesize impulsive sounds, such as thuds, slaps, taps, knocks, and rattles. These new methods can be used to examine the joint time-frequency characteristics of a sound, to select individual components based on their time-frequency localization, to quantify the components, and to synthesize new sounds from the selected components. The new tools will be presented in a non-mathematical way illustrated by two real-life sound quality problems, extracting the impulsive components of a windshield wiper sound, and analyzing a door closing-induced rattle.

Scalograms based on shift-invariant orthonormal wavelet transforms can be used to analyze impulsive and transient sounds in the presence of more stationary sound backgrounds, such as wind noise or drivetrain noise. The visual threshold of detection for impulsive features on the scalogram (signal energy content vs. time and frequency,) is shown to be similar to the audible threshold of detection of the human auditory system for the corresponding impulsive sounds. Two examples of impulsive sounds in a realistic automotive sound background are presented: automotive interior rattle in a vehicle passenger compartment, and spark knock recorded in an engine compartment.

This work describes a single camera based object distance estimation system. As technology on vehicles is constantly advancing on the road to autonomy, it is critical to know the locations of objects in 3D space for safe behavior of the vehicle. Though significant progress has been made on object detection in 2D sensor space from a single camera, this work additionally estimates the distance to said object without requiring stereo vision or absolute knowledge of vehicle motion. Specifically, our proposed system is comprised of three modules: vision based ego-motion estimation, object-detection, and distance estimation. In particular, we compensate for the vehicle ego-motion by using pin-hole camera model to increase the accuracy of the object distance estimation.

A DMS (Driver Monitoring System) is one of the most important safety features that assist in the monitoring functions and alert drivers when distraction or drowsiness is detected. The system is based in a DSMC (Driver Status Monitoring Camera) mounted in the vehicle's dash, which has a predefined set of operational requirements that must be fulfilled to guarantee the correct operation of the system. These conditions represent a trade space analysis challenge for each vehicle since both the DSMC and the underlying vehicle’s requirements must be satisfied. Relying upon the camera’s manufacturer evaluation for every iteration of the vehicle’s design has proven to be time-consuming, resources-intensive, and ineffective from the decision-making standpoint.

The United States Department of Transportation (USDOT) and the Crash Avoidance Metrics Partnership-Vehicle Safety Communications 2 (CAMP-VSC2) Consortium (Ford, General Motors, Honda, Mercedes-Benz, and Toyota) initiated, in December 2006, a three-year collaborative effort in the area of wireless-based safety applications under the Vehicle Safety Communications-Applications (VSC-A) Project. The VSC-A Project developed and tested Vehicle-to-Vehicle (V2V) communications-based safety systems to determine if Dedicated Short Range Communications (DSRC) at 5.9 GHz, in combination with vehicle positioning, would improve upon autonomous vehicle-based safety systems and/or enable new communications-based safety applications.

Recent trends show a growing demand for improved powertrain noise and vibration quality. In particular, there is little customer acceptance of vibration and noise (“boom”) at engine idle speeds. CAE analysis is being used increasingly as an aid for reducing overall vehicle level responses. Traditionally, analytical idle response is evaluated for only one particular engine order at a time. An efficient Excel based tool called VeCTRA (Vehicle Cascade & Target Response Analysis) was developed to accurately assess the effects of multiple powertrain orders on the vehicle level idle response. VeCTRA is capable of predicting the overall vehicle level response (tactile and acoustic) as well as determining the contribution from each engine order and the specific component excitations within an order. VeCTRA is capable of using analytical or experimentally measured sensitivity and/or excitation data.

Ford Motor Company’s assembly plants build vehicles in a certain sequence. The planned sequence for the plant’s trim and final assembly area is developed centrally and is sent to the plant several days in advance. In this work we present the study of two cases where the plant changes the planned sequence to cope with production constraints. In one case, a plant pulls ahead two-tone orders that require two passes through the paint shop. This is further complicated by presence in the body shop area of a unidirectional rotating tool that allows efficient build of a sequence “A-B-C” but heavily penalizes a sequence “C-B-A”. The plant changes the original planned sequence in the body shop area to the one that satisfies both pull-ahead and rotating tool requirements. In the other case, a plant runs on lean inventories. Material consumption is tightly controlled down to the hour to match with planned material deliveries.

A key ingredient in designing products that are more robust is a thorough knowledge of the physics of the ideal function of those products and the physics of the failure modes of those products. We refer to the mathematical functions describing this physics as the transfer functions for that product. Dimensional analysis (DA) is a well known, but often overlooked, tool for reducing the number of experiments needed to characterize a physical system. In this paper, we demonstrate how the application of DA can be used to reduce the size of a DOE needed to estimate transfer functions experimentally. Furthermore, the transfer function generated using DOEs with DA tend to be more general than those generated using larger DOEs directly on the design parameters. With ever-increasing competitive pressure and reduced product development time, a tool such as DA, which can dramatically reduce experimental cost, is an incredibly valuable addition to an engineers toolbox.

To support its recycling efforts, Ford Motor Company is using a Raman based instrument, the RP-1, co-developed with SpectraCode Inc. to identify unknown polymeric parts. Our recycling initiative involves detailed dismantling of our vehicles into individual parts, calculating the percentage recyclability and making recommendations for the future use of recycled polymers. While Ford has voluntarily adopted the SAE J1344 marking protocol for identifying part material composition, a large number of unmarked parts still exist and require identification. This identification is being done with the help of RP-1. To facilitate this identification, we have generated an accurate reference library of Raman spectra for comparison to those of unknown materials. This paper will describe the techniques that were used to develop and refine the RP-1 reference library to identify automotive polymers, especially black/dark plastics.

A methodology is developed that incorporates high resolution CFD flowfield information and a particle trajectory simulation, aimed at addressing Paint Transfer Efficiency (PTE) for bell sprayers. Given a solid model for the bell sprayer, the CFD simulation, through automeshing, determines a high resolution Cartesian volume mesh (14-20 million cells). With specified values of the initial shaping air, transient and steady-state flow field information is obtained. A particle trajectory visualization tool called SpraySIM uses this complicated flowfield information to determine the particle trajectories of the paint particles under the influence of drag, gravity and electrostatic potential. The sensitivity of PTE on shaping air velocity, charge-to-mass ratio, potential, and particle diameter are examined.

People and their communities are looking for transportation solutions that reduce travel time, improve well-being and accessibility, and reduce emissions and traffic congestion. Although new mobility services like ride-hailing advertise improvements in these areas, closer inspection has revealed a discrepancy between industry claims and reality. Key decision-makers, including citizens, cities and enterprise, and mobility service providers have the opportunity to leverage connected vehicle and connected device data through cloud-based APIs. We propose a GHG data analytics framework that functions on top of a cloud platform to provide unique system-level perspectives on operating transportation services, from procuring the most environmentally and people friendly vehicles to scheduling and designing the services based on data insights.

As part of a continuing Ford Motor Company program to improve the seating packages of production cars, a simplified in-plant method was developed to check seating variations in production vehicles. The method also provided information helpful in determining causal factors when any irregularities were found. Equipment necessary for checking was designed to be easily transported to any site.

Wavelets are a powerful mathematical tool used to multi-resolution time-frequency decomposition of signals, in order to analyze them in different scales and obtain different aspects of the information. Despite being a relatively new tool, wavelets have being applied in several areas of human knowledge, especially in signal processing, with emphasis in encoding and compression of image, video and audio. Based on a previous successful applications (FRAZIER, 1999) together a commitment to quality results, this paper evaluates the use of the Discrete Wavelet Transform (DWT) as an compression algorithm to reduce the amount of data collected in road load signals (load history) which are used by the durability engineering teams in the automotive industry.

Until recently, tool & die making was a very traditional industry, relying on extensive know-how accumulated over decades of practice. Essentially, it remained a two stage-process: engineering/manufacture, followed by tryout/productionization. Improvements focused on engineering and production methods, but tryout remained the exclusive domain of the die maker. At last, advances in computer modeling methods and the adoption of aggressive lean management principles have brought transformational changes to the tryout phase. At the same time, new safety and weight imperatives have increased the penetration of advanced materials, whose formability characteristics are quite different from mild steels. This paper will explore how these advanced materials affect this transformation.

Swirl plane Particle Image Velocimetry (PIV) measurements were performed in a single-cylinder optically accessible gasoline direct injection (DISI) engine using a borescope introduced through the spark plug hole. This allowed the use of a contoured piston and the visualization of the flow field in and around the piston bowl. The manifold absolute pressure (MAP) was fixed at 90 kPa and the engine speed was varied in increments of 250 rpm from 750 rpm to 2000 rpm. Images were taken from 270° to 320° bTDC of compression at 10° intervals to study the evolution of the velocity fluctuations. Measurements were performed with and without fuel injection to study its effect on the in-cylinder flow fields. Fuel was injected at 10 MPa and 5 MPa. The 2-D spatial mean velocities of individual flow fields and their decompositions were averaged over 100 cycles and used to investigate the effects of engine speed and image timing on the flow field.

The effect of friction modifiers on the low-speed frictional properties of automatic transmission fluids (ATFs) was investigated by scanning force microscopy (SFM). A clutch lining material was covered by a droplet of test ATF, and a steel tip was scanned over the sample. The scanning speeds were varied from 0.13 to 8.56 mm /sec, and the frictional force was deduced from the torsion of the SFM cantilever. A reduction in dynamic friction due to the addition of the friction modifier was clearly observed over the entire speed range. This indicates that the boundary lubrication mechanism is dominant under this condition, and therefore surface-active friction modifiers can effectively improve the frictional characteristics. The friction reduction was more pronounced at lower sliding speeds. Thus addition of friction modifiers produced a more positive slope in the μ-ν (friction vs. sliding speed) plots, and would contribute to make wet clutch systems less susceptible to shudder vibrations.

There are a multitude of dynamics faced by any industry. There is also a consistent search and development of technological platforms and services to address these changes. This necessitates a shared work philosophy which involves multiple stakeholders. Verification and validation are integral part of any development irrespective of product, process, or services. Also, every industry has a regulatory compliance to adhere too. But the extent of complexity and the level of dependencies or interactions between modules as well as stakeholders involved, creates slippage at some or other level. Nowadays the industries are also driven by reuse for cost effectiveness. Though it marks the significant improvement in the capability to compete, compatibility is a key measure to a successful product or service launch and sustainability.

Morphological features of voids were characterized for T300/924 12-ply and 16-ply composite laminates at different porosity levels through the implementation of a digital microscopy (DM) image analysis technique. The composite laminates were fabricated through compression molding. Compression pressures of 0.1MPa, 0.3MPa, and 0.5MPa were selected to obtain composite plaques at different porosity levels. Tension-tension fatigue tests at load ratio R=0.1 for composite laminates at different void levels were conducted, and the dynamic stiffness degradation during the tests was monitored. Fatigue mechanisms were then discussed based on scanning electron microscope (SEM) images of the fatigue fracture surfaces. The test results showed that the presence of voids in the matrix has detrimental effects on the fatigue resistance of the material, depending on the applied load level.

Flanging is a secondary operation in sheet metal forming processes. Traditionally, the design of flange shape and trim line is based on an engineer's experience. It takes several iterations to achieve the desired flange geometry because of potential splits. In this paper, an efficient CAE-based tool is developed to quickly predict the formability of a given flange design and enable the optimization of trim lines. A numerical algorithm is formulated in this CAE tool to convert the 3D flanging process into an equivalent in-plane deformation problem. The developed CAE tool is also integrated with the optimization software LS-OPT for trim line design.