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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’.

Metal panels are comprehensively applied in the automotive industry. A significant issue with metal panels is the deflection when moving in the press line of the stamping process. Unpredictable deflection could result in the cut off of the press line. To control the deflection in a safe zone, finite element tools are used to simulate the panel transform process. However, the simulation requires experimental validation where conventional displacement measurement techniques could not satisfy the requirement of vast filed displacement and accuracy point tracking. In this study, multi-camera digital image correlation (DIC) systems have been developed to track the movement of panels during the press line of the stamping process. There are some advantages of applying the DIC system, including non-contact, full-field, high accuracy, and direct measurement techniques that provide the evaluation displacement of the metal panel and press line.

Current implementations of vision-based Advanced Driver Assistance Systems (ADAS) are largely dependent on real-time vehicle camera data along with other sensory data available on-board such as radar, ultrasonic, and GPS data. This data, when accurately reported and processed, helps the vehicle avoid collisions using established ADAS applications such as Forward Collision Avoidance (FCA), Autonomous Cruise Control (ACC), Pedestrian Detection, etc. Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) over Dedicated Short Range Communication (DSRC) provides basic sensory data from other vehicles or roadside infrastructure including position information of surrounding traffic. Exchanging rich data such as vision data between multiple vehicles, and between vehicles and infrastructure provides a unique opportunity to advance driver assistance applications and Intelligent Transportation Systems (ITS).

Autonomous vehicle navigation, both global and local, makes use of large amounts of multifactorial data from onboard sensors, prior information, and simulations to safely navigate a chosen terrain. Additionally, as each mission has a unique set of requirements, operational environment and vehicle capabilities, any fixed formulation for the cost associated with these attributes is sub-optimal across different missions. Much work has been done in the literature on finding the optimal cost definition and subsequent mission pathing given sufficient measurements of the preference over the mission factors. However, obtaining these measurements can be an arduous and computationally expensive task. Furthermore, the algorithms that utilize this large amount of multifactorial data themselves are time consuming and expensive.

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.

Electronic Speckle Pattern Interferometry (ESPI) is the most sensitive and accurate method for 3D deformation measurement in micro and sub micro-level. ESPI measures deformation by evaluating the phase difference of two recorded speckle interferograms under different loading conditions. By a spatial phase shift technique, ESPI allows for the rapid, accurate and continuous 3D deformation measurement. Multi-channel and carrier frequency are the two main methods of spatial phase shift. Compared with carrier frequency method, which is subject to the problem of spectrum aliasing, multi-channel method is more flexible in use. For extracting the phase value of speckles, four-step algorithm and five-step arbitrary phase algorithm are commonly used. Different algorithms have different spatial resolution, operational requirements, and phase image quality.

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.

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.

Future fully autonomous and partially autonomous cars equipped with Advanced Driver Assistant Systems (ADAS) should assure safety for the pedestrian. One of the critical tasks is to determine if the pedestrian is crossing the road in the path of the ego-vehicle, in order to issue the required alerts for the driver or even safety breaking action. In this paper, we investigate the use of 2D pose estimators to determine the direction and speed of the pedestrian crossing the road in front of a vehicle. Pose estimation of body parts, such as right eye, left knee, right foot, etc… is used for determining the pedestrian orientation while tracking these key points between frames is used to determine the pedestrian speed. The pedestrian orientation and speed are the two required elements for the basic path estimation.

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.

Inter-vehicle communication is being considered as a means for increasing safety and efficiency in future intelligent highways. However, the security in these future mobile ad hoc networks of vehicles should not be an after thought. The main challenges in developing such security schemes are the highly dynamic environment and the cost restrictions. In this paper, we propose a keyless scheme for message authentication in inter-vehicle communication by verifying the sender’s position and velocity. The approach relies on signal propagation time to authenticate messages being communicated. No infrastructure or dedicated hardware beyond standard GPS is required.

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.

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.

The development of efficient algorithms has been the focus of automobile engineers since self-driving cars become popular. This is due to the potential benefits we can get from self-driving cars and how they can improve safety on our roads. Despite the good promises that come with self-driving cars development, it is way behind being a perfect system because of the complexity of our environment. A self-driving car must understand its environment before it makes decisions on how to navigate, and this might be difficult because the changes in our environment is non-deterministic. With the development of computer vision, some key problems in intelligent driving have been active research areas. The advances made in the field of artificial intelligence made it possible for researchers to try solving these problems with artificial intelligence. Lane detection and tracking is one of the critical problems that need to be effectively implemented.

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.

Digital shearography has many advantages, such as full-field, non-contact, high sensitivity, and good robustness. It was widely used to measure the deformation and strain of materials, also to the application of nondestructive testing (NDT). However, most digital sherography applications can only work in one field of view per measurement, and some small defects may not be detected as a result. Multiple measurements of different fields of view are needed to solve this issue, which will increase the measurement time and cost. The difficulty in performing multiple measurements may also increase for cases where the loading is not repeatable. Therefore, a system capable of measuring dual fields of view at the same time is necessary. The carrier frequency spatial phase shift method may be a good candidate to reach this goal because it can simultaneously record phase information of multiple images, e.g. two speckle interferograms with different fields of view.

Durability of automotive structures is a primary engineering consideration that is evaluated during a vehicle's design and development. In addition, it is a basic expectation of consumers, who demand ever-increasing levels of quality and dependability. Automakers have developed corporate requirements for vehicle system durability which must be met before a products is delivered to the customer. To provide early predictions of vehicle durability, prior to the construction and testing of prototypes, it is necessary to predict the forces generated in the vehicle structure due to road inputs. This paper describes an application of the “virtual proving ground” approach for vehicle durability load prediction for a vehicle on proving ground road surfaces. Correlation of the results of such a series of simulations will be described, and the modeling and simulation requirements to provide accurate simulations will be presented.

The complete lifecycle of complex systems, such as ground vehicles, consists of multiple phases including design, manufacturing, operation and sustainment (O&S) and finally disposal. For many systems, the majority of the lifecycle costs are incurred during the operation and sustainment phase, specifically in the form of uncertain maintenance costs. Testing and analysis during the design phase, including reliability and supportability analysis, can have a major influence on costs during the O&S phase. However, the cost of the analysis itself must be reconciled with the expected benefits of the reduction in uncertainty. In this paper, we quantify the value of performing the tests and analyses in the design phase by treating it as imperfect information obtained to better estimate uncertain maintenance costs.

Fatigue life estimation, reliability and durability are important in acquisition, maintenance and operation of vehicle systems. Fatigue life is random because of the stochastic load, the inherent variability of material properties, and the uncertainty in the definition of the S-N curve. The commonly used fatigue life estimation methods calculate the mean (not the distribution) of fatigue life under Gaussian loads using the potentially restrictive narrow-band assumption. In this paper, a general methodology is presented to calculate the statistics of fatigue life for a linear vibratory system under stationary, non-Gaussian loads considering the effects of skewness and kurtosis. The input loads are first characterized using their first four moments (mean, standard deviation, skewness and kurtosis) and a correlation structure equivalent to a given Power Spectral Density (PSD).

Dang Van (Dang Van et al., 1982 and Dang Van, 1993) states that for an infinite lifetime (near fatigue limit), crack nucleation in slip bands may occur at the most unfavorable oriented grains, which are subject to plastic deformation even if the macroscopic stress is elastic. Since the residual stresses in these plastically deformed grains are induced by the restraining effect of the adjacent grains, it is assumed that the residual stresses are stabilized at a mesoscopic level. These stresses are currently approximated by the macroscopic hydrostatic stress defined by the normal stresses to the faces of an octahedral element oriented with the faces symmetric to the principal axis; mathematically they are equal to each other and they are the average of the principal stresses.