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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 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.  

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.

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.

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.

There are several variables to consider when specifying a hydraulic hybrid system in a commercial vehicle. Parameters which can be controlled include various component sizes and some hybrid system calibration parameters. Presenter Paul Schwark, Bosch Rexroth AG

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 The development, analysis, and optimization of battery electric class-7 heavy-duty trucks equipped with multi-speed transmissions are discussed in this paper. The designs of five new traction motors-fractional-slot, concentrated winding machines-are proposed for use in heavy-duty electric trucks. The procedure for gear-ratio range selection is outlined and ranges of gear ratios for three-to six-speed transmission powertrains are calculated for each of the proposed electric traction motors. The simulation and gear-ratio optimization tasks for class-7 battery electric trucks are formulated. The energy consumption of the e-truck with the twenty possible powertrain combinations is minimized over the four driving cycles and the most efficient powertrain layouts that meet the performance criteria are recommended.

Abstract In this article, a unique design for Hydro-Pneumatic Energy Harvesting Suspension HPEHS system is introduced. The design includes a hydraulic rectifier to maintain one-way flow direction in order to obtain maximum power generation from the vertical oscillation of the suspension system and achieve handling and comfort car drive. A mathematical model is presented to study the system dynamics and non-linear effects for HPEHS system. A simulation model is created by using Advanced Modeling Environment Simulations software (AMEsim) to analyze system performance. Furthermore, a co-simulation platform model is developed using Matlab-Simulink and AMEsim to optimize the PID controller parameters of the external variable load resistor applied on the generator by using Particle Swarm Optimization (PSO).

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 A new concept of instantaneous wheel turn center (IWTC) is proposed to evaluate and improve multi-axle vehicle steering coordination performance. The concept of IWTC and its calculation method are studied. The index named dispersion of IWTC is developed to evaluate the vehicle steering coordination performance quantitatively. The simulation tests based on a three-axle off-road vehicle model are conducted under different vehicle velocities and lateral accelerations. The simulation results show that the turn centers of different wheels are disperse, and the dispersion becomes larger with the increase of vehicle velocities and lateral acceleration. Since suspension has important influences on vehicle steering performance, the genetic algorithm is used to optimize the suspension hard points and bushing stiffness, aiming at minimizing the dispersion of wheel turn centers (DWTC) to improve the vehicle steering coordination performance.

Abstract This research developed methods for a virtual operator model (VOM) to learn the optimal control inputs for operation of a virtual excavator. Virtual design, used to model, simulate, and test new features, has often been limited by the fidelity of the virtual model of human operators. Human operator learns, over time, the capability, limits, and control characteristics of new vehicles to develop the best strategy to maximize the efficiency of operation. However, VOMs are developed with fixed strategies and for specific vehicle models (VMs) and require time-consuming re-tuning of the VOM for each new vehicle design. Thus, there typically is no capability to optimize strategies, taking account of variation in vehicle capabilities and limitations. A VOM learning capability was developed to optimize control inputs for the swing-to-pile task of a trenching operation. Different control strategies consisted of varied combinations of speed control, position control, and coast.

Abstract In order to improve robustness of vehicle dynamic performance, a steering mechanism model is proposed with alignment parameters of front wheel based on preference function method. In the steering mechanism model controllable variables include the trapezoid connection length, the base angle of steering trapezoid, the kingpin inclination angle, caster, camber and uncontrollable variables include load and initial braking velocity. Optimization objective is some vehicle dynamic performance. In the preference function method the individual performance preference and preference aggregation in designing variable space and performance variable space are analyzed. The individual performance preference includes the controllable variable preference, noise factor preference and optimization objective preference. The aggregation function is developed by aggregating all the individual performance preferences.

Abstract This article investigates the fuel savings potential of a series hybrid military truck using a simultaneous battery pack design and powertrain supervisory control optimization algorithm. The design optimization refers to the sizing of the lithium-ion battery pack in the hybrid configuration. The powertrain supervisory control optimization determines the most efficient way to split the power demand between the battery pack and the engine. Despite the available design and control optimization techniques, a generalized mathematical formulation and solution approach for combined design and control optimization is still missing in the literature. This article intends to fill that void by proposing a unified framework to simultaneously optimize both the battery pack size and power split control sequence. This is achieved through a combination of genetic algorithm (GA) and Pontryagin’s minimum principle (PMP) where the design parameters are integrated into the Hamiltonian function.

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 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.

The ride comfort of the commercial vehicle is mainly affected by several vibration isolation systems such as the primary suspension system, engine mounting system and the cab mounting system. A rigid-flexible coupling model for the truck was built and analyzed in multi-body environment (ADAMS). The method applying the excitation on the wheels center and the engine mountings in time domain was presented. The variables' effects on the ride performance were studied by design of experiment (DOE). The optimal design was obtained by the co-simulation of the ADAMS/View, iSIGHT and Matlab. It was found that the vertical root mean square (RMS) acceleration and frequency-weighted RMS acceleration on the seat track were reduced about 17% and 11% respectively at different speeds relative to baseline according to ISO 2631-1.