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As vacuum suction cups are widely used in stamping plants, it becomes urgent and important to understand their performance and failure mode. Vacuum suction cups are employed to lift, move, and place sheet metal instead of human hands. Occasionally the vacuum cups would fail and drop parts, even it would cause expensive delays in the production line. In this research, several types of vacuum cups have been studies and compared experimentally. A new tensile device and test method was developed to measure the pulling force and deformation of vacuum cups. The digital image correlation technique has been adopted to capture and analyze the contour, deformation and strain of the cups under different working conditions. The experimental results revealed that the relevant influential parameters include cup type, pulling force angles, vacuum levels, sheet metal curvatures, etc.

An objective evaluation of ground vehicle performance is a challenging task. This is further exacerbated by the increasing level of autonomy, dynamically changing the roles and capabilities of these vehicles. In the context of decision making involving these vehicles, as the capabilities of the vehicles improve, there is a concurrent change in the preferences of the decision makers operating the vehicles that must be accounted for. Decision based methods are a natural choice when multiple conflicting attributes are present, however, most of the literature focuses on static preferences. In this paper, we provide a sequential Bayesian framework to accommodate time varying preferences. The utility function is considered a stochastic function with the shape parameters themselves being random variables. In the proposed approach, initially the shape parameters model either uncertain preferences or variation in the preferences because of the presence of multiple decision makers.

The classical definition of reliability may not be readily applicable for repairable systems. Commonly used concepts such as the Mean Time Between Failures (MTBF) and availability can be misleading because they only report limited information about the system functionality. In this paper, we discuss a set of metrics that can help with the design of repairable systems. Based on a set of desirable properties for these metrics, we select a minimal set of metrics (MSOM) which provides the most information about a system, with the smallest number of metrics. The metric of Minimum Failure Free Period (MFFP) with a given probability generalizes MTBF because the latter is simply the MFFP with a 0.5 probability. It also generalizes availability because coupled with repair times it provides a clearer picture of the length of the expected uninterrupted service. Two forms of MFFP are used: transient and steady state.

In this paper, the development of random vibration testing schedules for durability design verification of engine mounted products is presented, based on the equivalent fatigue damage concept and the 95th-percentile customer engine usage data for 150,000 miles. Development of the 95th-percentile customer usage profile is first discussed. Following that, the field engine excitation and engine duty cycle definition is introduced. By using a simplified transfer function of a single degree-of-freedom (SDOF) system subjected to a base excitation, the response acceleration and stress PSDs are related to the input excitation in PSD, which is the equivalent fatigue damage concept. Also, the narrow-band fatigue damage spectrum (FDS) is calculated in terms of the input excitation PSD based on the Miner linear damage rule, the Rayleigh statistical distribution for stress amplitude, a material's S-N curve, and the Miles approximate solution.

An existing challenge in current state-of-the-art autonomous vehicles is the process of safely transferring control from autonomous driving mode to manual mode because the driver may be distracted with secondary tasks. Such distractions may impair a driver’s situational awareness of the driving environment which will lead to fatal outcomes during a handover. Current state-of-the-art vehicles notify a user of an imminent handover via auditory, visual, and physical alerts but are unable to improve a driver’s situational awareness before a handover is executed. The overall goal of our research team is to address the challenge of providing a driver with relevant information to regain situational awareness of the driving task. In this paper, we introduce a novel approach to estimating a driver’s visual focus of attention using a 2D RGB camera as input to a Multi-Input Convolutional Neural Network with shared weights. The system was validated in a realistic driving scenario.

In this paper, we develop a methodology to enable the isolation of the heat release contribution of knocking combustion from flame-propagation combustion. We first address the empirical modeling of individual non-autoigniting combustion history using the Wiebe function, and subsequently apply this methodology to investigate the effect of autoignition on the heat release history of knocking cycles in a spark ignition (SI) engine. We start by re-visiting the Wiebe function, which is widely used to model empirically mass burned histories in SI engines. We propose a method to tune the parameters of the Wiebe function on a cycle-by-cycle basis, i.e., generating a different Wiebe to suitably fit the heat release history of each cycle. Using non-autoigniting cycles, we show that the Wiebe function can reliably simulate the heat release history of an entire cycle, if only data from the first portion of the cycle is used in the tuning process.

Through the study of the straightening theory, the major causes of the errors affecting straightening accuracy have been analyzed. An error-perturbation curve has been generated from the difference between experiments and the single point straightening theory. By the study of this disturb error curve, a correction value can be obtained. Using this value to compensate the press stroke, the precise straightening result can be achieved.

The Intelligent Ground Vehicle Competition (IGVC) is a multidisciplinary exercise in product realization for college engineering students. They design, build, and compete with autonomous vehicles in events ranging from lane following, obstacle avoidance, platooning, to Global Positioning System (GPS) navigation. Technologies involved include electronic controls, computer-based vision systems, object detection, rangefinding, and global positioning. The real world applications are in intelligent transportation systems, the military, and manufacturing automation. Students have been creative and have learned a great deal. Industry recruiters have been highly supportive.

Reliability and resiliency (R&R) definitions differ depending on the system under consideration. Generally, each engineering sector defines relevant R&R metrics pertinent to their system. While this can impede cross-disciplinary engineering projects as well as research, it is a necessary strategy to capture all the relevant system characteristics. This paper highlights the difficulties associated with defining performance of such systems while using smart microgrids as an example. Further, it develops metrics and definitions that are useful in assessing their performance, based on utility theory. A microgrid must not only anticipate load conditions but also tolerate partial failures and remain optimally operating. Many of these failures happen infrequently but unexpectedly and therefore are hard to plan for. We discuss real life failure scenarios and show how the proposed definitions and metrics are beneficial.

Light-weighting vehicles cause an increase in Aluminum Alloy stamping processes in the Automotive Industry. Surface finish and lubricants of aluminum alloy (AA) sheet play an important role in the deep drawing processes as they can affect the friction condition between the die and the sheet. This paper aims to develop a reliable and practical laboratory test method to experimentally investigate the influence of surface finish, lubricant conditions, draw-bead clearances and pulling speed on the frictional sliding behavior of AA 6XXX sheet metal. A new double-beads draw-bead-simulator (DBS) system was used to conduct the simulated test to determine the frictional behavior of an aluminium alloy with three surface lubricant conditions: mill finish (MF) with oil lube, electric discharge texture (EDT) finish with oil lube and mill finish (MF) with dry lube (DL).

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’.

Off-road vehicle operation requires constant decision-making under great uncertainty. Such decisions are multi-faceted and range from acquisition decisions to operational decisions. A major input to these decisions is terrain information in the form of soil properties. This information needs to be propagated to path planning algorithms that augment them with other inputs such as visual terrain assessment and other sensors. In this sequence of steps, many resources are needed, and it is not often clear how best to utilize them. We present an integrated approach where a mission’s overall performance is measured using a multiattribute utility function. This framework allows us to evaluate the value of acquiring terrain information and then its use in path planning. The computational effort of optimizing the vehicle path is also considered and optimized. We present our approach using the data acquired from the Keweenaw Research Center terrains and present some results.

This paper proposes a new nonlinear model predictive control (NMPC) for autonomous vehicle path tracking problem. The vehicle is equipped with active rear steering, allowing independent control of front and rear steering. Traditional NMPC, which runs at fixed sampling rate, has been shown to provide satisfactory control performance in this problem. However, the high throughput of NMPC limits its implementation in production vehicle. To address this issue, we propose a novel event-triggered NMPC formulation, where the NMPC is triggered to run only when the actual states deviate from prediction beyond certain threshold. In other words, the event-triggered NMPC will formulate and solve a constrained optimal control problem only if it is enabled by a trigger event. When NMPC is not triggered, the optimal control sequence computed from last NMPC instance is shifted to determine the control action.

Tubular hydroforming is a novel process that has recently gained much attention due to its cost-effective application in the automotive industry. Hydroformed automotive parts have high strength to weight ratio and have good repeatability with high dimensional accuracy. At this time, there is little experience in modeling the hydroforming process to better understand its application and researchers have tried using stamping simulation software to analyze the process. Unlike conventional sheet stamping which is a displacement driven process, tubular hydroforming is a force driven process and its success is governed by the nature of internal pressurization. Hence, a new three-dimensional finite element model using a computationally efficient 6-noded shell element has been developed. A simple pressure prediction model has been developed and integrated into the formulation for effective control of the process.

Autonomous vehicles might one day be able to implement privacy preserving driving patterns which humans may find too difficult to implement. In order to measure the difference between location privacy achieved by humans versus location privacy achieved by autonomous vehicles, this paper measures privacy as trajectory anonymity, as opposed to single location privacy or continuous privacy. This paper evaluates how trajectory privacy for randomized driving patterns could be twice as effective for autonomous vehicles using diverted paths compared to Google Map API generated shortest paths. The result shows vehicles mobility patterns could impact trajectory and location privacy. Moreover, the results show that the proposed metric outperforms both K-anonymity and KDT-anonymity.

Springback is a common phenomenon in automotive manufacturing processes, caused by the elastic recovery of the internal stresses during unloading. A thorough understanding of springback is essential for the design of tools used in sheet metal forming operations. A DBS (Draw-bead Simulator) has been used to simulate the forming process for two different sheet metals: aluminum and steel. Two levels of pulling force and two die radii have been enforced to the experimental process to get different springback. Also, the Digital Image Correlation (DIC) system has been adopted to capture the sheet contour and measure the amount of side-wall-curl (sheet springback) after deformation. This paper presents the influence of the material properties, force, and die radius on the deformation and springback after forming. A thorough understanding of this phenomenon is essential, seeing that any curvature in the part wall can affect quality and sustainability.

In order to constrain the restraining force and control the speed of metal flow, drawbeads are widely used in industry. They prevent wrinkling or necking in formed panels, reduce the binder force, and minimize the usage of sheet metal to make a part. Different drawbead configurations can satisfy various stamping production. Besides local design of drawbeads, other factors like pulling directions, binder angles and single or multiple beads play an important role too. Moreover, it was found that the same beads configuration can own a different rate of change of pulling force on different gaps by experience. In this paper, to study the effect of each factor, the Aluminum and Steel sheet metals were tested to obtain the pulling force as they passed through a draw bead. Three gap cases between a male and a female beads are set to figure out the trend of pulling force.

Polymer plastics are widely used in automotive light weight design. Tensile tests are generally used to obtain material stress-strain curves. Due to the natural of the plastic materials, it could be elongated more than several hundred percent of its original length before breaking. Digital Image Correlation (DIC) Analysis is a precise, full field, optical measurement method. It has been accepted as a practical in-field testing method by the industry. However, with the traditional single-camera or dual-camera DIC system, it is nearly impossible to measure the extreme large strain. This paper introduces a unique experimental procedure for large elongation measurement. By utilization of quad-camera DIC system and data stitch technique, the strain history for plastic material under hundreds percent of elongation can be measured. With a quad-camera DIC system, the correlation was conducted between two adjacent cameras.

In Aluminum Alloy, AA, sheet metal forming, the through thickness cracking at the edge of cut out is one of the major fracture modes. In order to prevent the edge cracking in production forming process, practical edge stretch limit criteria are needed for virtual forming prediction and early stamping trial evaluations. This paper proposes new methods for determining the edge stretching limit of the sheet coupons, with and without pre-stretching, based on the Digital Image Correlation (DIC) technique. A numbers of sets of notch-shaped smaller coupons with three different pre-stretching conditions (near 5%, 10% and fractured) are cut from the prestretched large specimens. Then the notch-shaped smaller coupons are stretched by uniaxial tension up to through edge cracking observed. A dual-camera 3D-DIC system is utilized to measure both coupon face strain and thickness strain in the notch area at the same time.

Dimensional problems for punched holes on a sheet metal stamping part include being undersized and oversized. Some important relationships among tools and products, such as the effect of conical punch tip angle, are not fully understood. To study this effect, sheets of AA6016 aluminum and BH210 steel were punched by punches with different conical tip angles. The test method and test results are presented. The piercing force and withdrawing force when using conical punches were also studied. The results indicate that the oversize issue for a punched hole in a stamped panel is largely due to the combination of the conical tip effect and the stretching-release effect.