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As part of a continuous research and innovation effort, Ford Motor Company has been evaluating hydrogen as an alternative fuel option for vehicles with internal combustion engines since 1997. Ford has recently designed and built an Econoline (E-450) shuttle bus with a 6.8L Triton engine that uses gaseous hydrogen fuel. Safe practices in the production, storage, distribution, and use of hydrogen are essential for the widespread public and commercial acceptance of hydrogen vehicles. Hazards and risks inherent in the application of hydrogen fuel to internal combustion engine vehicles are explained. The development of a Hydrogen Management System (H2MS) to detect hydrogen leaks in the vehicle is discussed, including the evolution of the H2MS design from exploration and quantification of risks, to implementation and validation of a working system on a vehicle. System elements for detection, mitigation, and warning are examined.

Generally within engineering design, the current emphasis is on biasing the development process towards increased virtual prototyping and reduced “real” prototyping. Therefore there is a requirement for more CAE based automated optimisation, Design of Experiments and Design for Six Sigma. The main requirements for these processes are that the model being analysed is parametric and that the solution time is short. Prediction of gear whine behaviour in automatic transmissions is a particularly complex problem where the conventional FEA approach precludes the rapid assessment of “what if?” scenarios due to the slow model building and solution times. This paper will present an alternative approach, which is a fully parametric functionality-based model, including the effects of and interactions between all components in the transmission. In particular the time-varying load sharing and misalignment in the planetary gears will be analysed in detail.

A series of ceria and ceria-zirconia supported Pd model automotive catalysts were prepared and aged under air or redox conditions at 1050°C for 12 h. The supports were manufactured by different methods and represent a range of compositions. The samples were characterized before and after aging by BET, X-ray diffraction, mercury porosimetry, XPS, H2 temperature-programmed reduction, and oxygen storage capacity measurements. Oxygen storage measurements revealed that the behavior of the catalysts varied according to aging conditions and temperature of measurement. Pd/ceria-zirconia catalysts showed higher oxygen storage characteristics after 1050°C aging than Pd/ceria catalysts, and the phase purity of the ceria-zirconia was shown to positively affect the amount of oxygen storage. The initial rates of oxygen release from the model catalysts at 350°C were shown to depend on the preparation conditions of the supports.

This paper presents some of the design rules used to calculate critical geometry of engine components, and the object-oriented component hierarchy system in PET. This paper also presents parametric solid model assembling schemes used to dynamically construct an assembly of whole powertrain systems. Some examples of powertrain concept design, such as the estimation of friction, packaging, and moving component clearances, will be presented. The computational efficiency of this concept design method will be compared to traditional methods also.

Static seating bucks have long been used as the only means to subjectively appraise the vehicle interior packages in the vehicle development process. The appraisal results have traditionally been communicated back to the requesting engineers either orally or in a written format. Any design changes have to be made separately after the appraisal is completed. Further, static seating bucks lack the flexibility to accommodate design iterations during the evolution of a vehicle program. The challenge has always been on how to build a seating buck quickly enough to support the changing needs of vehicle programs, especially in the early vehicle development phases. There is always a disconnect between what the seating buck represents and what is in the latest design (CAD), since it takes weeks or months to build a seating buck and by the time it is built the design has already been evolved. There is also no direct feedback from seating buck appraisal to the design in CAD.

The high conversion efficiency required by the modern three-way catalyst (TWC) is dependent on oxygen storage material functionality and capacity. To successfully model a TWC, it is critical that the oxygen storage function in the catalyst be adequately represented. The original oxygen storage model (a simple “bucket” model) included in one of Ford's TWC models, SIMTWC, was developed for vehicle programs meeting LEV emission standards. Application of SIMTWC to test data from vehicles targeting more stringent emission standards, such as ULEV and PZEV, revealed limitations in the accuracy of the original bucket model. To address these limitations, an improved kinetic model of oxygen storage is being developed. This new model is more kinetically-detailed than the old model.

Global concerns involving smog, ozone formation, carcinogens and greenhouse gases have produced increasingly stringent governmental emission regulations worldwide. In the United States, the Environmental Protection Agency (EPA) introduced Tier II emissions regulations and the California Air Resources Board (CARB) established Low Emission Vehicles (LEV II) and Partial Zero Emission Vehicles (PZEV) legislation. These initiatives have created the most stringent emissions regulations to date. Vehicle manufacturers have had to improve their evaporative emission control systems to comply with these standards. The evaporative emission control system is engineered to protect our environment from fuel vapor emissions. The carbon canister is the most important component of the evaporative emissions system due to its ability to capture fuel vapors continuously during the life of the vehicle. Ford Motor Company redesigned its carbon canisters after utilizing Experimental Design techniques.

The Snook tables (Liberty Mutual Tables) are a collection of data sets compiled from studies based on a psychophysical approach to material-handling tasks. These tables are used to determine safe loads for lifting, lowering, carrying pulling, and pushing. The tables take into account different population percentiles, gender, and frequency of activity. However, while using these tables to analyze a work place, Ergonomists often have to select from discrete data points closest to the actual work place parameters thereby reducing accuracy of results. To compound the problem further, multiple interrelated variables are involved, making it difficult to analyze parameters intuitively. For example, it can be difficult to answer questions such as, does reducing the lifting height lower the recommended lifting weight, if the lifting distance is increased? To resolve such issues, this paper presents a new methodology for implementing the Snook tables using multi variable regression.

Selective catalytic reduction (SCR) is a technology capable of meeting Tier 2 Bin 5 emissions levels of oxides of nitrogen (NOX) for diesel engines. Base metal zeolite catalysts show the best combination of thermal durability and NOX conversion activity. It is shown in this work that some base metal zeolite catalysts can store high levels of hydrocarbons (HCs). Also, base metal zeolite catalysts can catalyze oxidation of HCs under certain conditions. Oxidation of stored hydrocarbons can lead to permanent catalyst deactivation due to the exotherm generated in the SCR catalyst (over-temperature condition leading to SCR catalyst damage). This paper discusses a laboratory bench test to characterize hydrocarbon storage and burn-off characteristics of several SCR catalyst formulations, as well as engine dynamometer tests showing hydrocarbon storage and exotherm generation.

Binary Logistic Regression is a powerful tool to apply in Six Sigma projects, when the response is characterized as an attribute. This paper has the purpose to present a case study based on Binary Logistic Regression application in a Six Sigma DMAIC project, where the output of the process could only be measured as “component assembled Ok or component assembled Not Ok” - a binary response.

The relation cost versus performance in the design of an automobile is crucial for its success. These two characteristics, much like the project development timing, are closely related to the attributes that the new design must achieve (e.g. weight, fuel economy, torsional stiffness, NVH, safety, etc.). In this respect, the design optimization of body reinforcements (i.e. part thickness, quantity of reinforcements, and number of spot welds) contributes greatly to a sound and robust project concept. This paper describes one application of 6-Sigma methodology to evaluate the performance of different configurations of seat belt reinforcements resulting in an optimized concept that achieved the proposed performance targets with weight and sub-assembly complexity reduction. Using a Design of Experiments (DOE) and Finite Element Analysis (FEA), each proposal was evaluated for its resistance to plastic deformation.

This paper explores the interrelation of Six Sigma and TRIZ. The use of Six Sigma DMAIC and/or DCOV principles with merging of inventive principles of TRIZ is a suggestion of paths forward to reduce the time to solve problems. The search for solutions is paralyzed in some circumstances because of psychological inertia because of it is natural for people to rely on their own experience and not think outside their comfort spot. Six Sigma pollinated with TRIZ is an opportunity to find the ideal final result. A case study on a Truck Turn Signal is used to illustrate the idea.

Six Sigma represents a mindset change – part of this mindset, is to focus our decision based on data, looking for the root causes of our issues instead of acting on the effects of the causes. Aligned to this statement, the purpose of this paper is to present through a case study, how the concepts of Six Sigma – a data driven mindset, can be used to improve a process, reducing waste and keeping the same standards of quality. The focus is to show how a transfer function, generated through a multiple regression can optimize a production process, reducing waste and improving quality.

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.

Six-Sigma provides the opportunity and discipline to eliminate mistakes, improve morale, and save money. Doing things right and keeping them consistent is the idea behind Six-Sigma. A fundamental objective of Six-Sigma is to achieve customer satisfaction with continuous improvement in quality. Process control and manufacturing variation reduction is important but companies often find that the majority of their quality problems were actually created during the design process. An example of improving manufacturing process capability to give bottom line cost savings and customer satisfaction is presented in this paper. The methodology to increase system robustness through Design for Six Sigma (DFSS) is presented and demonstrated through the extension of the case study of crankshaft journal lobing design robustness improvements.

Design for Six Sigma (DFSS) is a systematic process and a disciplined problem prevention approach to achieve business excellence. Robust design is the heart of DFSS. To enable the success of robust parameter design, one should start with good design concept. Axiomatic Design, a fundamental set of principles that determine good design practice, can help to facilitate a project team to accelerate the generation of good design concept. Axiomatic Design holds that uncoupled designs are to be preferred over coupled design. Although uncoupled designs are not always possible, application of axiomatic design principles in DFSS presents an approach to help DFSS team focus on functional requirements to achieve design intents and maximize product reliability. As a result of the application of axiomatic design followed by parameter design, the DFSS team achieved design robustness and reliability. A hydraulic lash adjuster case study will be presented.

Shielding a vehicle underbody is becoming a daunting task with increased exhaust temperatures due to emissions regulations and ever-increasing packaging constraints, which place components ever closer to exhaust systems. This experimental study was initiated to evaluate the two dimensional thermal effects of heat shield flange height and shield width in vehicle underbody idle conditions. The ultimate goal of this study is to develop a function to optimize the shape of heat shielding to achieve a specified floorpan temperature during vehicle idle conditions.

“Doing the right things” is important for a company to stay in business while developing the right products to satisfy customers and make profits. Design for Six Sigma (DFSS) is a disciplined problem prevention approach and a systematic process to prevent defects in what is important to the customer. This paper builds on the rationale and opportunities presented in the SAE paper of Six Sigma Disciplines in Automotive Applications for improving design robustness. The methodology to increase system robustness through DFSS is presented and demonstrated through the extension of the case study of crankshaft journal lobing design robustness improvements realized from the traditional DMAIC Six Sigma project presented in the SAE paper of Six Sigma Disciplines in Automotive Applications.

Automotive operations experience substantial financial losses when any one item, from a set of vehicle-specific sequenced parts, is unavailable. Justifying the appropriate buffer size using “heuristics” is increasingly difficult as “lean” advocates push for smaller inventories. One costly scenario is the painted body buffer in operations where the sequence of parts for final assembly is determined prior to the start of the paint process. To provide an objective methodology for determining buffer building capacity and target fill level, we developed a cost optimization model. This demonstrates, graphically, the criticality of proper buffer sizes and the cost effectiveness of designing the final assembly operations with the capability of short-term storage for a small amount (2 - 10) of sequenced parts, when the expected painted body is not available. The model is easily modified to suit a particular situation, by revising the input parameters to more appropriate values.

Six Sigma is a comprehensive and flexible methodology for achieving, maintaining, and maximizing business success by sustaining a disciplined use of facts, data, and statistics while managing, improving, and reinventing business processes based on customer requirements and cost targets. Six Sigma is a holistic approach to reducing concerns tied directly to achieving organizational objectives. AutoAlliance uses structured processes based on problem-solving methodologies known as D-M-A-I-C: define - measure - analyze - improve - control. Six Sigma deployment involves hard work, frustration, starts/stops, and disappointments that go along with launching a long-term culture change. AutoAlliance's goal is to have the entire workforce utilizing the methodologies in their everyday work. At that point, the “Six Sigma” change is complete.