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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.  

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.

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.

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.

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.

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.

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.

Recent fluctuation in oil prices has generated interest in fuel-efficient vehicles, especially their aerodynamic profile. The literature indicates that turbulent wakes that form at the rear end of the vehicle contribute to vehicle drag in a major way. Minor studies have addressed the effects of rear-end wall angle to the drag force through effecting the wake behind the vehicle; however, this study assesses the reduction of drag using angular side walls. A previous simulation of external airflow over Ahmed's body was investigated, utilizing the k-ω SST models. Different angles of side walls were analyzed, and a maximum 36.85% reduction in drag coefficient was achieved using an angular rear side wall. The turbulent model was validated and the effectiveness of angular rear side walls thus proven. The study then simulated the flow for a road vehicle model to investigate the real world effect of angular rear side walls.

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.

This paper describes the development and testing of a Dynamic Vibration Absorber to reduce frame beaming vibration in a highway tractor. Frame beaming occurs when the first vertical bending mode of the frame is excited by road or wheel-end inputs. It is primarily a problem for driver comfort. Up until now, few options were available to resolve this problem. The paper will review the phenomenon, design factors affecting a vehicle's sensitivity to frame beaming, and the principles of Dynamic Vibration Absorbers (AKA Tuned Mass Dampers). Finally, the paper will describe simulation and testing that led to the development of an effective vibration absorber as a field fix.

This paper focuses on the manufacturer's conflict in the conceptual design of commercial vehicles between highly customized special vehicles and the greatest possible degree of standardization. Modularity and standardization are crucial success factors for realizing high variance at the best cost efficiency in development and production as well for achieving the highest quality standards at reduced efforts for technical validation. The presented virtual design approach for commercial vehicle concepts allows for purposeful design and integration of new concepts and technologies on the component level in an existing product portfolio - not neglecting manufacture's portfolio requirements concerning standardization and modularity. The integrated tool chain helps to bring trade-offs to a head that exist in balancing between dedicated vehicles with best customer-relevant characteristics and standardized vehicles with the highest degree of commonality.

A novel speed and position dependent Lane Keeping Assistance (LKA) control strategy for heavy vehicles is proposed. This LKA system can be implemented with any torque overlay system capable of accepting external position or torque commands. The proposed algorithm tackles the problem of lane keeping in two ways from a heavy vehicle's perspective. First, it stabilizes the vehicle's lateral position by bringing it to the center of the lane and giving it the correct heading to stay there. This is done using a speed and position dependent control strategy that becomes less aggressive as the vehicle's speed increases and as it gets closer to the center of the lane. Such speed and position dependency is especially critical in heavy vehicles where unnecessary aggressive control can lead to oscillations about the lane's centerline when cruising at high speeds.

Terrestrial winds play an important role in affecting the aerodynamics of road vehicles. Of increasing importance is the effect of the unsteady turbulence structure of these winds and their influence on the process of optimizing aerodynamic performance to reduce fuel consumption. In an effort to predict better the aerodynamic performance of heavy-duty vehicles and various drag reduction technologies, a study was undertaken to measure the turbulent wind characteristics experienced by heavy-duty vehicles on the road. To measure the winds experienced on the road, a sport utility vehicle (SUV) was outfitted with an array of four fast-response pressure probes that could be arranged in vertical or horizontal rake configurations that provided measurements up to 4.0 m from the ground and spanning a width of 2.4 m. To characterize the influence of the proximity of the vehicle on the pressure signals of the probes, the SUV and its measurements system was calibrated in a large wind tunnel.

In tire development, the dynamic tire-road contact forces are an important indicator to assess structure-borne interior cabin noise. This type of noise is the dominant source in the frequency range from 50-450 Hz, especially when rolling with constant angular velocity on a rough road. The spatial force distribution is difficult or sometimes even impossible to simulate or measure in practice. So, the use of an inverse technique is proposed. This technique uses response measurements in combination with a digital twin simulation model to obtain the input forces in an inverse way. The responses and model properties are expressed in the time domain, since it is specifically aimed to trace back the impact locations from road surface texture indents on the tire. In order to do so, the transient responses of the travelling waves as a result of these impacts is used. The framework expresses responses as a convolution product of the unknown loads and impulse response measurements.

Due to recent infrastructural development and emerging competitive automotive markets, there is seen a huge shift in customer’s demand and vehicle drivability pattern in commercial vehicle industry. Now apart from ensuring better vehicle durability and best in class tyre life and fuel mileage, a vehicle manufacturer also has to focus on other key attributes like driver’s safety and ride comfort. Thus, for ensuring enhanced drivability, key parameters for ensuring better vehicle handling includes optimization of bump steer and brake steer. Both bump steer and brake steer are vehicle’s undesirable phenomenon where a driver is forced to constantly make steering wheel correction in order to safely maneuver the vehicle in the desired path.

Driving cycles are typically used for estimation of vehicle fuel/energy consumption and CO2 emissions. In most of applications only the vehicle velocity vs. time profile is considered as a driving cycle, while a road slope is typically omitted. Since the road slope significantly impacts the fuel consumption, it should be included into realistic driving cycles for hilly roads. As a part of wider research of multidimensional driving cycle synthesis, this paper focuses on analysis of a broad city bus driving cycle dataset recorded in the city of Dubrovnik. The analysis is aimed at revealing the impact of road slope on velocity and acceleration distributions, and clustering the recorded data into several groups reflecting various driving and traffic congestion characteristics. Finally, the Markov chain method is employed to synthesize 3D driving cycles for the selected data clusters, where the Markov chain states include vehicle velocity, vehicle acceleration, and road slope.

Lift axle is essentially provided in commercial vehicles to increase the vehicle’s load-carrying capacity. The axle is lowered in the case of a high payload and the load is evenly distributed among the wheels both on fixed axles and the lift axle. This ability to lift the axle implies better maneuverability in turns, better fuel consumption, and less wear and tear on the tires and brake shoes. Also, it will reduce the damage to the road surfaces. This lowering and lifting of the lift axle are controlled by a series of valves together called the Lift Axle Control System (LACS). This LACS must consider the vehicle load condition, the ignition state, and gear state to decide if the axle must be lifted or lowered. This paper deals with the modeling and simulation of the LACS system at the vehicle level and optimize the design for the respective desired design solution.

Despite numerous research efforts, there is no reliable and widely accepted tool for the prediction of erosion prone material surfaces due to collapse of cavitation bubbles. In the present paper an Erosion Aggressiveness Index (EAI) is proposed, based on the pressure loads which develop on the material surface and the material yield stress. EAI depends on parameters of the liquid quality and includes the fourth power of the maximum bubble radius and the bubble size number density distribution. Both the newly proposed EAI and the Cavitation Aggressiveness Index (CAI), which has been previously proposed by the authors based on the total derivative of pressure at locations of bubble collapse (DP/Dt>0, Dα/Dt<0), are computed for a cavitating flow orifice, for which experimental and numerical results on material erosion have been published. The predicted surface area prone to cavitation damage, as shown by the CAI and EAI indexes, is correlated with the experiments.