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This course is verified by Probitas as meeting the AS9104/3A requirements for Continuing Professional Development. Advanced product quality planning (APQP) is essential to improving the way companies develop products and services.  It is a standardized, universally accepted fundamental business strategy. This strategy is applicable to all types of organizations including manufacturing and service companies, schools, hospitals, and governmental agencies. The aim of APQP is to enable the organization to produce products and provide services focused on satisfying customer’s needs, wants, and expectations.  

Design of Experiments is a statistically based, structured approach to product or process improvement that will quickly yield significant increases in product quality and subsequent decreases in cost.  Products and processes can be designed to function with less variation and with less sensitivity to environmental factors or customer usage. While still maintaining high quality from a customer's viewpoint, products and processes can utilize lower cost materials and methods.  Specifications can be opened-up with wider tolerances while still maintaining high quality for customers.  

This course introduces the highly mathematical field of control systems focusing on what the classical control system tools do and how they can be applied to automotive systems. Dynamic systems, time/frequency responses, and stability margins are presented in an easy to understand format. Utilizing Matlab and Simulink, participants will learn how simple computer models are generated. Other fundamental techniques in control design such as PID and lead-lag compensators will be presented as well as the basics of embedded control systems.

This course is offered in China only and presented in Mandarin Chinese. The course materials are bilingual (English and Chinese). Currently in the industry, especially within China, product requirement development is more of an experience-based process rather than a scientific methodology. This course addresses this issue and provides a more process-driven method for better requirement development through the Quality Function Deployment (QFD) methodology.  Real industrial examples are used to demonstrate how to systematically convert the voice of the customer data to engineering specifications using QFD.

The Process FMEA and Control Plan program introduces the basic concepts behind this important tool and provides training in how to conduct an effective PFMEA. First, the course explains what a PFMEA is and how it improves the long-term performance of your products, services and related processes by addressing process related failures. The role of the PFMEA in the overall framework of Quality Management System Requirements is explained as well as the role of the PFMEA in the Advanced Product Quality Planning (APQP) process. Additionally, the differences and relationships between the DFMEA and PFMEA are well defined.

The concept of a Quality System’s approach to business has been employed successfully and sometimes not so successfully for several decades. The International Organization for Standardization (ISO) has been supplying standards that list the key elements/clauses and requirements for building and implementing Quality Systems for over 30 years. These standards are based on the relatively simple concepts of Total Quality Management (TQM), essential principals of management, and a “Process” approach. These standards have been revised several times over the years to make them more realistic and user friendly.

During this DFMEA Overview and Application course, participants will be introduced to important FMEA concepts, the basic theory behind the concepts, then discuss how these concepts can be applied to the customer's design FMEA activities. Participant activities include: reading assignments, group discussions, exercises, building Block Diagrams as a group, and beginning a DFMEA on a customer’s product.

Vehicle functional requirements, emission regulations, and thermal limits all have a direct impact on the design of a powertrain cooling airflow system. Given the expected increase in emission-related heat rejection, suppliers and vehicle manufacturers must work together as partners in the design, selection, and packaging of cooling system components. The goal of this two-day course is to introduce engineers and managers to the basic principles of cooling airflow systems for commercial and off-road vehicles.

Design of Experiments (DOE) is a methodology that can be effective for general problem-solving, as well as for improving or optimizing product design and manufacturing processes. Specific applications of DOE include identifying proper design dimensions and tolerances, achieving robust designs, generating predictive math models that describe physical system behavior, and determining ideal manufacturing settings. This course utilizes hands-on activities to help you learn the criteria for running a DOE, the requirements and pre-work necessary prior to DOE execution, and how to select the appropriate designed experiment type to run.

RMS (Reliability-Maintainability-Safety-Supportability) engineering is emerging as the newest discipline in product development due to new credible, accurate, quantitative methods. Weibull Analysis is foremost among these new tools. New and advanced Weibull techniques are a significant improvement over the original Weibull approach. This workshop, originally developed by Dr. Bob Abernethy, presents special methods developed for these data problems, such as Weibayes, with actual case studies in addition to the latest techniques in SuperSMITH® Weibull for risk forecasts with renewal and optimal component replacement.

Advanced vehicular thermal management system can improve engine performance, minimize fuel consumption, and reduce emissions by harmoniously operating computer-controlled servomotor components. In this paper, a neural network-based optimal control strategy is proposed to regulate the engine temperature through the advanced cooling system. Presenter Asma Al Tamimi, Hashemite University

Battery Electric Vehicles and Extended Range Electric Vehicles, like the Chevrolet Volt, can use electrical energy from the Grid to meet the majority of a driver�s transportation needs. This has the positive societal effects of displace petroleum consumption and associated pollutants from combustion on a well to wheels basis, as well as reduced energy costs for the driver. CO2 may also be lower, but this depends upon the nature of the grid energy generation. There is a mix of sources � coal-fired, gas -fired, nuclear or renewables, like hydro, solar, wind or biomass for grid electrical energy. This mix changes by region, and also on the weather and time of day. By monitoring the grid mix and communicating it to drivers (or to their vehicles) in real-time, electrically driven vehicles may be recharged to take advantage of the lowest CO2, and potentially lower cost charging opportunities.

EGR coolers are used in combustion engines to reduce NOx emissions. However, heat transfer in these coolers also results in thermophoresis-temperature-gradient driven motion of suspended particles towards cooler regions-which leads to significant soot deposition. Presenter Meisam Mehravaran

The number of electronically controlled systems in commercial vehicles is increasing rapidly. Much of this electrical content is controlled using ECUs (Electronic Control Units) which share information using some type of networking technology, such as a CAN bus running the SAE J1939 protocol. Presenter Jeffrey Craig, Vector CANtech Inc.

This technical paper collection contains 53 technical papers. Topics covered include engine exhaust aftertreatment and integration; hybrid vehicle integration and optimization; powertrain and drivetrain NVH; advanced transmission and driveline component design; diesel engine system design; fuel economy; alternative fuels; and advanced engine component design.

Abstract Exhaust manifolds are one of the most important components on the engine assembly, which is mounted on engine cylinder head. Exhaust manifolds connect exhaust ports of cylinders to the turbine for turbocharged diesel engine therefore they play a significant role in the performance of engine system. Exhaust manifolds are subjected to very harsh thermal loads; extreme heating under very high temperatures and cooling under low temperatures. Therefore designing a durable exhaust manifold is a challenging task. Computer aided engineering (CAE) is an effective tool to drive an exhaust manifold design at the early stage of engine development. Thus advanced CAE methodologies are required for the accurate prediction of temperature distribution. However, at the end of the development process, for the design verification purposes, various tests have to be carried out in engine dynamometer cells under severe operating conditions.

Abstract Although ground grading is one of the most common tasks that hydraulic excavators perform in typical work sites, proper grading is not easy for less-skilled operators as it requires coordinated manipulation of multiple hydraulic cylinders. In order to help alleviate this difficulty, automated grading systems are considered as an effective alternative to manual operations of hydraulic excavators. In this article, a sliding mode controller design is presented for automated grading control of a hydraulic excavator. First, an excavator manipulator model is developed in Simulink by using SimMechanics and SimHydraulics toolboxes. Then, a sliding mode controller is designed to control the manipulator to trace a predefined trajectory for a grading task. For a comparison study, a PI controller is used to control the manipulator to perform a grading task following the same desired trajectory and the performance is compared with those obtained by the sliding mode controller.

Abstract Reliability analysis of a large-scale system under random dynamic loads can be a very time-consuming task since it requires repeated studies of the system. In many engineering problems, for example, wave loads on an offshore platform, the excitation loads are defined using a power spectral density (PSD) function. For a given PSD function, one needs to generate many time histories to make sure the excitation load is modeled accurately. Global and local approximation methods are available to predict the system response efficiently. Each way has their advantages and shortcomings. The combined approximations (CA) method is an efficient method, which combines the advantages of local and global approximations. This work demonstrates two methodologies that utilize CA to reduce the cost of crude or separable Monte Carlo simulation (MCS) of linear dynamic systems when the excitation loads are defined using PSD functions.

Abstract This study investigates methods to precisely control a coolant pump in an internal combustion engine. The goal of this research is to minimize power consumption while still meeting optimal performance, reliability and durability requirements for an engine at all engine-operating conditions. This investigation achieves reduced fuel consumption, reduced emissions, and improved powertrain performance. Secondary impacts include cleaner air for the earth, reduced operating costs for the owner, and compliance with US regulatory requirements. The study utilizes mathematical modeling of the cooling system using heat transfer, pump laws, and boiling analysis to set limits to the cooling system and predict performance changes.

Road vibrations cause fatigue failures in vehicle components and systems. Therefore, reliable and accurate damage and life assessment is crucial to the durability and reliability performances of vehicles, especially at early design stages. However, durability and reliability assessment is difficult not only because of the unknown underlying damage mechanisms, such as crack initiation and crack growth, but also due to the large uncertainties introduced by many factors during operation. How to effectively and accurately assess the damage status and quantitatively measure the uncertainties in a damage evolution process is an important but still unsolved task in engineering probabilistic analysis. In this paper, a new procedure is developed to assess the durability and reliability performance, and characterize the uncertainties of damage evolution of components under constant amplitude loadings.