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Countless articles and publications3,4,5 have documented and proven the efficacy, benefits and value of operating within a lean system. Furthermore, there exists common agreement amongst leading organizations successfully implementing a lean system that in order to do so it must take into consideration the entire enterprise, that is, from supplier to customer and everything in between6. One of the core issues this paper addresses is when the optimal time is to train and educate the people who currently have, or will have, influence over the ‘enterprise’.

A variety of structures resonate when they are excited by external forces at, or near, their natural frequencies. This can lead to high deformation which may cause damage to the integrity of the structure. There have been many applications of external devices to dampen the effects of this excitation, such as tuned mass dampers or both semi-active and active dampers, which have been implemented in buildings, bridges, and other large structures. One of the active cancellation methods uses centrifugal forces generated by the rotation of an unbalanced mass. These forces help to counter the external excitation force coming into the structure. This research focuses on active force cancellation using centrifugal forces (CFG) due to mass imbalance and provides a virtual solution to simulate and predict the forces required to cancel external excitation to an automotive structure. This research tries to address the challenges to miniaturize the CFG model for a body-on-frame truck.

A challenge for the aerodynamic optimization of trucks is the limited availability of wind tunnels for testing full scale trucks. FAW wants to introduce a development process which is mainly based on CFD simulation in combination with some limited amount of wind tunnel testing. While maturity of CFD simulation for truck aerodynamics has been demonstrated in recent years, a complete validation is still required before committing to a particular process. A 70% scale model is built for testing in the Shanghai Automotive Wind Tunnel Center (SAWTC). Drag and surface pressures are measured for providing a good basis for comparison to the simulation results. The simulations are performed for the truck in the open road driving condition as well as in an initial digital model of the aerodynamic wind tunnel of SAWTC. A full size truck is also simulated in the open road driving condition to understand the scaling effect.

Nitridng usually improves wear resistance and can be accomplished using a gas or plasma method; it's necessary to find if there is any difference in surface roughness, wear and/or wear mechanism when choosing between methods for nitriding. In this study, Ball-on-disk wear test was compared on coupons nitrided with five different nitriding cycles that processed at temperatures of 500-570°C, with a processing time of 8 - 80 hrs. Different compound layer thicknesses were formed, (5-8μm), and a minimum of 0.38 mm case depth was produced. Nitrided samples were also compared to nitrocarburized and the nitrided coupons with a “0” compound layer in a ball-on-disk test. Few selected coupons were post-polished and wear test on ball-on-disk test was compared with the coupons without post polishing. Optical surface roughness using White Light Interferometry (WLIM) and metallurgical testing was performed.

The residual stresses found in components are mainly due to thermal, mechanical and metallurgical changes of material. The manufacturing processes such as fabrication, assembly, welding, rolling, heat treatment, shot peening etc. generate residual stresses in material. The influence of residual stress can be beneficial or detrimental depending on nature and distribution of the residual stress in material. In general, the compressive residual stress can increase the fatigue life of material because it provides greater resistance for crack initiation and propagation. A significant number of improvements for residual stress measurement techniques have occurred in last few decades. The most popular technique of residual stress measurement is based on the principle of strain gage rosette and hole drilling (ASTM E837-01, destructive).

Vehicle front panel is an interior part which has a major impact on the consumers’ experience of the vehicles. To keep a good appearance during long time aging period, most of the front panel is designed as a rough surface. Some types of surface defects on the rough surface can only be observed under the exposure of certain angled sun light. This brings great difficulties in finding surface defects on the production line. This paper introduces a novel polarized laser light based surface quality inspection method for the rough surfaces on the vehicle front panel. By using the novel surface quality inspection system, the surface defects can be detected real-timely even without the exposure under certain angled sun light. The optical fundamentals, theory derivation, experiment setup and testing result are shown in detail in this paper.

This research studies the transformation kinetics of austempered ductile iron (ADI) with and without nickel as the main alloying element. ADI has improved mechanical properties compared to ductile iron due to its ausferrite microstructure. Not only can austempered ductile iron be produced with high strength, high toughness and high wear resistance, the ductility of ADI can also be increased due to high carbon content austenite. Many factors influence the transformation of phases in ADI. In the present work, the addition of nickel was investigated based on transformation kinetics and metallography observation. The transformation fractions were determined by Rockwell hardness variations of ADI specimens. The calculation of transformation kinetics and activation energy using the “Avrami Equation” and “Arrhenius Equation” is done to describe effects of nickel alloy for phase reactions.

Scuffing is a failure mechanism which can occur in various engineering components, such as engine cylinder kits, gears and cam/followers. In this research, the scuffing behavior of 4140 steel and ductile iron was investigated and compared through ball-on-disk scuffing tests. A step load of 22.2 N every two minutes was applied with a light mineral oil as lubricant to determine the scuffing load. Both materials were heat treated to various hardness and tests were conducted to compare the scuffing behavior of the materials when the tempered hardness of each material was the same. Ductile iron was found to have a consistently high scuffing resistance before tempering and at tempering temperatures lower than 427°C (HRC ≻45). Above 427°C the scuffing resistance decreases. 4140 steel was found to have low scuffing resistance at low tempering temperatures, but as the tempering temperature increases, the scuffing resistance increased.

Mobility in the automotive and transportation sectors has been experiencing a period of unprecedented evolution. A growing need for efficient, clean and safe mobility has increased momentum toward sustainable technologies in these sectors. Toward this end, battery electric vehicles have drawn keen interest and their market share is expected to grow significantly in the coming years, especially in light-duty applications such as passenger cars. Although the battery electric vehicles feature high performance and zero tailpipe emission characteristics, economic and technical issues such as battery cost, driving range, recharging time and infrastructure remain main hurdles that need to be fully addressed. In particular, the low power density of the battery limits its broad adoption in heavy-duty applications such as class 8 semi-trailer trucks due to the required size and weight of the battery and electric motor.

A significant amount of residual stresses can be developed in aluminum castings during heat treatment. This paper reports an experimental study of the residual stress distributions in aluminum castings after solution treatment and water quench. The residual stresses in aluminum castings are measured using both optical and resistance strain rosettes. The optical strain rosette technique was recently developed in conjunction with ring-core cutting method for residual stress measurement. The measured residual stresses from optical and resistance strain rosettes are compared with the results of X-ray and neutron diffraction measurements. The advantages and disadvantages of various measurement methods are discussed.

Optimizing the trade-off between reliability and cost of operating a microgrid, including vehicles as both loads and sources, can be a challenge. Optimal energy management is crucial to develop strategies to improve the efficiency and reliability of microgrids, as well as new communication networks to support optimal and reliable operation. Prior approaches modeled the grid using MATLAB, but did not include the detailed physics of loads and sources, and therefore missed the transient effects that are present in real-time operation of a microgrid. This article discusses the implementation of a physics-based detailed microgrid model including a diesel generator, wind turbine, photovoltaic array, and utility. All elements are modeled as sources in Simulink. Various loads are also implemented including an asynchronous motor. We show how a central control algorithm optimizes the microgrid by trying to maximize reliability while reducing operational cost.

Weight reduction is very important in automotive design because of stringent demand on fuel economy. Structural optimization of dynamic systems using finite element (FE) analysis plays an important role in reducing weight while simultaneously delivering a product that meets all functional requirements for durability, crash and NVH. With advancing computer technology, the demand for solving large FE models has grown. Optimization is however costly due to repeated full-order analyses. Reanalysis methods can be used in structural vibrations to reduce the analysis cost from repeated eigenvalue analyses for both deterministic and probabilistic problems. Several reanalysis techniques have been introduced over the years including Parametric Reduced Order Modeling (PROM), Combined Approximations (CA) and the Epsilon algorithm, among others.

High-fidelity finite element (FE) tire-snow interaction models have the advantage of better understanding the physics of the tire-snow system. They can be used to develop semi-analytical models for vehicle design as well as to design and interpret field test results. For off-terrain conditions, there is a high level of uncertainties inherent in the system. The FE models are computationally intensive even when uncertainties of the system are not taken into account. On the other hand, field tests of tire-snow interaction are very costly. In this paper, dynamic metamodels are established to interpret interaction forces from FE simulation and to predict those forces by using part of the FE data as training data and part as validation data. Two metamodels are built based upon the Krieging principle: one has principal component analysis (PCA) taken into account and the other does not.

Quality and performance are two important customer requirements in vehicle design. Driveline clunk negatively affects the perceived quality and must be therefore, minimized. This is usually achieved using engine torque management, which is part of engine calibration. During a tip-in event, the engine torque rate of rise is limited until all the driveline lash is taken up. However, the engine torque rise, and its rate can negatively affect the vehicle throttle response. Therefore, the engine torque management must be balanced against throttle response. In practice, the engine torque rate of rise is calibrated manually. This paper describes a methodology for calibrating the engine torque in order to minimize the clunk disturbance, while still meeting throttle response constraints. A set of predetermined engine torque profiles are calibrated in a vehicle and the transmission turbine speed is measured for each profile. The latter is used to quantify the clunk disturbance.

Spark plug design is critical for the performance of spark ignited (SI) engines, however, its orientation is frequently not controlled for most of production engines, which has great impacts on ignition and subsequent flame propagation processes. In the present work, a recently developed comprehensive ignition system model--the VTF ignition model, has been employed to investigate the effects of spark plug orientation on ignition and flame kernel growth. Three orientations for the spark plug, including downstream, crossflow, and upstream relative to the flow, have been considered under a typical a high-speed high-load condition in a GDI engine. Electrical circuitry model was validated by comparing the simulation results with measured secondary current and secondary voltage with good agreement.

Spot Welding is now widely used in the fabrication of sheet metals, mainly due to the cost and time considerations. Spot welds are found in nearly all products where sheet metal is joined. Examples range from a single metal toolbox to nearly 10,000 spot welds found in a typical passenger car. Obviously the quality of the spot weld has a direct impact on the quality of the product. The problem of estimating the spot-weld quality is an important component in quality control. If the weld nuggets are improperly or incompletely formed, or the area surrounding the nugget is smaller than required, the structural integrity of the entire part may be uncertain. Furthermore these inconsistencies are usually internal and are seldom visible to Optical Inspection. This study is focused on the non-destructive evaluation of the spot welds using “Digital Shearography”.

Polymer Electrolyte Membrane (PEM) fuel cells have grown in research and development for many applications due to their high efficiency and humble operating condition requirements. Water management in the cathode region of the PEM fuel cell is an essential and sensitive phenomenon for cold environments and fuel cell’s performance. This paper investigates the behavior of water production by constructing a transparent-cathode PEM fuel cell. The effects of pressure, relative humidity, and cathode stoichiometric ratio on the production of water as a function of time were studied. Each test set is compared to a reference state. The images of water liquid accumulation inside the cathode bipolar plate channels are shown with the corresponding polarization curves.

Engineering design-decisions often involve many attributes which can differ in the levels of their importance to the decision maker (DM), while also exhibiting complex statistical relationships. Learning a decision-making policy which accurately represents the DM’s actions has long been the goal of decision analysts. To circumvent elicitation and modeling issues, this process is often oversimplified in how many factors are considered and how complicated the relationships considered between them are. Without these simplifications, the classical lottery-based preference elicitation is overly expensive, and the responses degrade rapidly in quality as the number of attributes increase. In this paper, we investigate the ability of deep preference machine learning to model high-dimensional decision-making policies utilizing rankings elicited from decision makers.

The coefficient of friction between surfaces is an important criterion for predicting metal behavior during sheet metal stamping processes. This research introduces an innovative technique to find the coefficient of friction on a lubricated aluminum sheet metal surface by simulating the industrial manufacturing stamping process while using 3D digital image correlation (3D-DIC) to track the deformation. During testing, a 5000 series aluminum specimen is placed inside a Stretch-Bend-Draw Simulator (SBDS), which operates with a tensile machine to create a stretch and bend effect. The friction coefficient at the contact point between an alloy sheet metal and a punch tool is calculated using an empirical equation previously developed. In order to solve for the unknown friction coefficient, the load force and the drawback force are both required. The tensile machine software only provides the load force applied on the specimen by the load cell.

In the automotive industry, a Malfunction Indicator Light (MIL) is commonly employed to signify a failure or error in a vehicle system. To identify the root cause that has triggered a particular fault, a technician or engineer will typically run diagnostic tests and analyses. This type of analysis can take a significant amount of time and resources at the cost of customer satisfaction and perceived quality. Predicting an impending error allows for preventative measures or actions which might mitigate the effects of the error. Modern vehicles generate data in the form of sensor readings accessible through the vehicle’s Controller Area Network (CAN). Such data is generally too extensive to aid in analysis and decision making unless machine learning-based methods are used. This paper proposes a method utilizing a recurrent neural network (RNN) to predict an impending fault before it occurs through the use of CAN data.