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In order to maximize customer satisfaction in today's global market place, the quality of products and services need to be improved continually. Increased focus on quality, with the attendant proliferation of methods and tools, has created the need for a comprehensive framework to guide the selection of the tools. Individuals within an organization need to know what tools are appropriate in a given situation, and when, where and how the knowledge gained from an effort should be documented. In addition, a common nomenclature to convey quality related information to each other would avoid confusion and improve the communication process thus improving the effectiveness and productivity of the organization. This paper integrates tools that have evolved recently with the old tools that have been in use for a number of years.

Many descriptions of product development are based on a timeline of activity. Timelines typically do not characterize the underlying strategy and flexibility embodied in the technical activity that actually takes place between activity nodes. Timelines alone will inhibit evolving to a more rational approach to product development. The view of engineering described in this paper is a functional view of engineering. It is what engineers do. It is aligned with the technical tools used by engineers. It applies to both product development and manufacturing. It's purpose is to enhance understanding of the function of engineering activities, including reliability.

The use of finite element modeling (FEM) tools is part of the most of the current product development projects of the automotive industry companies, replacing an important part of the physical tests with lower costs, higher speed and with increasing accuracy by each day. In addition to this, computer-aided engineering (CAE) tools can be either used after the product is released, at any moment of the product life, in many different situation as a new feature release, to validate a more cost-efficient design proposal or to help on solving some manufacturing problem or even a vehicular field issue. Different from the phase where the product is still under development, when standard virtual test procedures are performed in order to validate the vehicle project, in this case, where engineers expertise plays a very important role, before to proceed with any standard test it is fundamental to understand the physics of the phenomena that is causing the unexpected behavior.

The capability to drive NVH quality into vehicle frame design is often compromised by the lack of available predictive tools that can be developed and applied within the timeframe during which key architectural design decisions are required. To address this need, a new parametric frame modeling approach was developed and is presented in this paper. This fully parameterized model is capable of fast modal, static stiffness & weight assessments, as well as DSA/optimization for frame design changes. This tool has been proven to be effective in improving speed, quality and impact of NVH hardware decisions.

The objective of this paper is to develop a test capable of ranking lift-gates based on strain concentration levels reflected in fringe characteristics in the known stress/strain concentration and fracture vicinity. First, the system (lift gate glass, adhesive and appliqué) is chosen as test sample since the subsystem (local appliqué) does not exhibit the failure mode observed in the field test. Subsequently, it has been identified that the thermal component (rather than mechanical) is the predominant load by laser scanning vibrometry and confirmed via field test data. Next, digital shearography has been selected as the measurement and visualization tool of strain distribution due to its various advantages such as full field view and non-contact advantages. Finally, the test method has been applied to rank and optimize the structural configuration around appliqués' to reduce / eliminate failure.

Distinguishing physical modes from mathematical modes in the modal analysis of complex systems, such as full vehicle structures, is a difficult and time-consuming process. The major tools frequently used are stabilization diagrams, mode indicator functions, or modal participation factors. When closely spaced modes are to be identified, the stabilization diagrams and mode indicator functions are no longer effective. Even the reciprocities of mode shapes and modal participation factors cannot be well satisfied to indicate whether a mode is a physical one, when measurement errors are large. To overcome these difficulties, an optimization procedure is developed, whereby physical modes can be sorted out in a given frequency range while the error between measured and synthesized frequency responses is minimized. An optimal subset selection algorithm is used in this procedure.

Modern vehicles become increasingly software intensive. Software development therefore is critical to the success of the manufacturer to develop state of the art technology. Standards like ISO 26262 recommend requirement-based verification and test cases that are derived from requirements analysis. Agile development uses continuous integration tests which rely on test automation and evaluation. All these drove the development of a new model-based software verification environment. Various aspects had to be taken into account: the test case specification needs to be easily comprehensible and flexible in order to allow testing of different functional variants. The test environment should support different use cases like open-loop or closed-loop testing and has to provide corresponding evaluation methods for continuously changing as well as for discrete signals.

An assessment tool was developed for rollover CAE signals evaluation to assess primarily the qualities of CAE generated sensor waveforms. This is a key tool to be used to assess CAE results as to whether they can be used for algorithm calibration and identify areas for further improvement of sensor. Currently, the method is developed using error estimates on mean, peak and standard deviation. More metrics, if necessary, can be added to the assessment tool in the future. This method has been applied to various simulated signals for laboratory-based rollover test modes with rigid-body-based MADYDO models.

Automotive companies have invested a fortune over the last three decades developing real-time embedded control strategies and software to achieve desired functions and performance attributes. Over time, these control algorithms have matured and achieved optimum behavior. The companies have vast repositories of embedded software for a variety of control features that have been validated and deployed for production. These software functions can be reused with minimal modifications for future applications. The companies are also constantly looking for new ways to improve the productivity of the development process that may translate into lower development costs, higher quality and faster time-to-market. All companies are currently embracing Model Based Design (MBD) tools to help achieve the gains in productivity. The most cost effective approach would be to reuse the available legacy software for carry-over features while developing new features with the new MBD tools.

Vehicle audio system performance is an important attribute for final costumers. In this sense, its evaluation is an important aspect for selecting the design and validation process for automobile manufacturers. Usually the vehicle audio system performance is evaluated only by subjective judgment. However the design requirements demands objective measurements to set targets establish benchmarking and apply refinements to the design. Thus, in order to evaluate and improve sound system performance, it has been established a subjective evaluation process on reproducing and analyzing customer perception in a more reliable way. To support this information, objective evaluations have been used based on total harmonic distortion (THD), normalized frequency response (NFR) methods and spectrogram, which have been shown as straight and fast objective tools. Reinforcing the objective evaluations, qualitative time-frequency spectrogram has been used.

Automotive manufacturing presents unique challenges for ergonomic analysis. The variety of tasks and frequencies are typically not seen in other industries. Moving these challenges into the realm of digital human modeling poses new challenges and offers the opportunity to create and enhance tools brought over from the traditional reactive approach. Chiang et al. (2006) documented an enhancement to the Siemen's Jack Static Strength Prediction tool. This paper will document further enhancements to the ErgoSolver (formerly known as the Ford Static Strength Prediction Solver).

To reduce warranty cost due to brake squeal and provide guidance for brake design, it is important to understand the contributions of key brake design parameters to brake noise. In this paper, a new technique, which employs the nonlinear transient finite element method as well as Taguchi method, is proposed as a design tool for improving the quality of brake systems. This DOE technique has been implemented to a car program. The final results identified the major parameters associated with the brake noise and also led to an optimal design by selecting appropriate levels of those parameters.

This paper highlights and discusses the development and deployment of an enterprise-level tool infrastructure that fits into the production build environment of Ford Motor Company. A particular focus is on navigating bottlenecks and pitfalls that arise with the adoption of a model-based software development process. This includes provisions to support centralized data and architecture artifact management (including version control across the lifecycle of the software), support to integrate and manage legacy software artifacts, support to archive and bookshelf development milestones, and last but not least, built-in intelligence to spot potential sources of software defects early in the development stage.

As systems necessarily become more integrated and increasingly complex through market demands for more features, technical risks and therefore business risks increase. It becomes correspondingly harder to show that the properties desired of these Systems of Systems (SoS) actually hold under normal or abnormal operation. In particular, it is hard to detect emergent properties of a SoS because properties of individual systems are not necessarily compositional, especially during failure. This paper describes the objectives of a project addressing the problem of Dependable System of Systems and other related research in the field of Automotive Electronics. The capability being developed is based upon the scalable ‘Assumption-Commitment’[1] paradigm so that it can be applied to large and complex systems of systems.

Lean Six Sigma is an approach that is gaining momentum both in manufacturing and service industries. Design for Lean Six Sigma (DFLSS) is an outgrowth of the DFSS and Lean Six Sigma approaches. The essence of DFLSS is to ensure design quality and predictability during the early design phases and the approach employs a structured integrated product development methodology and a comprehensive set of robust tools to drive product quality, innovation, faster time to market, and lower product costs. When it comes to automotive Product Development, applying lean principles and DFSS together becomes more of a challenge within the existing PD system. While the benefits of DFLSS present an attractive proposition in a fiercely competitive market it brings its own challenges as to how to deploy it for maximum benefits. This paper examines the challenges, potential and opportunities for DFLSS in the automotive industry and presents a vision for integrating it in to the Product Development System.

This paper discusses a Design For Six Sigma (DFSS) approach to a driveline system NVH design process as used on a RWD IRS (Independent Rear Suspension) vehicle program. It is shown how this approach helped understand the ways variability in the driveline system (mount properties and locations) affected output to the rest of the vehicle. A series of CAE and DFSS tools were used to deliver a distribution that described the vehicle Driveline Roughness performance, to identify the critical control factors that affected the performance, and to reduce the response sensitivity to variability of these critical factors. Other driveline issues were factored into the process indirectly.

Although great advances have been made over the last two decades in the automotive structural design process, tradition and experience guide many design choices even today. The need for innovative tools is stronger now more than ever before as the design engineer is confronted with more complex, often contradictory design requirements such as cost, weight, performance, safety, time to market, life cycle, aesthetics, environmental impact, changes in the industry's business models, etc. The ever-increasing use of optimization tools in engineering design generates solutions that are very close to the limits of the design constraints, hardly allowing for tolerances to compensate for uncontrollable factors such as manufacturing imperfections. Optimum designs developed without consideration of uncertainty can lead to non-robust designs.

Real-world second-by-second vehicle driving cycle data is very important for vehicle research and development. A project solely dedicated to generating such information would be tremendously costly and time consuming. Alternatively, we developed such a database by utilizing two publicly available passenger vehicle travel surveys: 2004-2006 Puget Sound Regional Council (PSRC) Travel Survey and 2011 Atlanta Regional Commission (ARC) Travel Survey. The surveys complement each other - the former is in low time resolution but covers driver operation for over one year whereas the latter is in high time resolution but represents only one-week-long driving operation. After analyzing the PSRC survey, we chose 382 vehicles, each of which continuously operated for one year, and matched their trips to all the ARC trips. The matching is carried out based on trip distance first, then on average speed, and finally on duration.

Throughout the evolution of transportation technology the automotive industry has continually devised methods of diagnosing and servicing vehicle electrical and electronic concerns. Methodologies have always included special test equipment accompanied by volumes of printed manual procedures. Today's vehicle technology, with its highly interactive/integrated systems control capability, has brought on a new level of complexity and confusion to the service technician. In order to assist the technician in the diagnosis of microprocessor based control systems, the service industry has developed highly sophisticated on-board vehicle diagnostics as well as off-board computer based equipment. This paper describes the progression of service test equipment provided by Ford Motor Company to assist in vehicle electrical/electronic diagnostics. Similar to all industry manufacturers Ford Motor has devised both on-board and off-board systems which are required to fix the car right the first time.

The primary coating layer that inhibits salt spray induced corrosion on vehicle bodies is electrocoat. The application of electrocoat involves the electrodeposition of a polymer film on all metallic components of the vehicle body after body construction. Particularly challenging in the electrocoat process is the deposition of the coating in recessed areas of the vehicle due to material and electrical current access constraints to those regions. Currently the verification of correct electrocoat coverage requires the use of costly tear-down prototypes. A simulation tool, called EPD, has been developed that predicts the electrocoat coverage on the full vehicle body. The tool allows engineers to identify areas where there may be issues with electrocoat coverage and to see the effect of vehicle design or process modifications on coverage. A challenge in the development of any simulation tool is computational speed.