Browse Topic: Reliability
Letter from the Guest Editors
This paper reviews the current situation in the terms and definitions that influence the development of testing and prediction in automotive, aerospace and other areas of engineering. The accuracy of these terms and definitions is very important for correct simulation, testing and prediction. This paper aims to define accurate terms and definitions. It also includes the author’s recommendations for improving this situation and preparing new standards.
Accurate object pose estimation refers to the ability of a robot to determine both the position and orientation of an object. It is essential for robotics, especially in pick-and-place tasks, which are crucial in industries such as manufacturing and logistics. As robots are increasingly tasked with complex operations, their ability to precisely determine the six degrees of freedom (6D pose) of objects, position, and orientation, becomes critical. This ability ensures that robots can interact with objects in a reliable and safe manner. However, despite advancements in deep learning, the performance of 6D pose estimation algorithms largely depends on the quality of the data they are trained on.
Since the early 1980s, the automotive industry has used hydraulically actuated (servo-hydraulic) test systems to simulate operating speeds and road conditions for testing OEM components and fully assembled vehicles. They have helped unlock vast improvements in the quality, safety, and reliability of the cars and trucks coming off the world’s assembly lines.
Video analysis plays a major role in many forensic fields. Many articles, publications, and presentations have covered the importance and difficulty in properly establishing frame timing. In many cases, the analyst is given video files that do not contain native metadata. In other cases, the files contain video recordings of the surveillance playback monitor which eliminates all original metadata from the video recording. These “video of video” recordings prevent an analyst from determining frame timing using metadata from the original file. However, within many of these video files, timestamp information is visually imprinted onto each frame. Analyses that rely on timing of events captured in video may benefit from these imprinted timestamps, but for forensic purposes, it is important to establish the accuracy and reliability of these timestamps. The purpose of this research is to examine the accuracy of these timestamps and to establish if they can be used to determine the timing
This paper introduces an innovative digital solution for the categorization and analysis of fractures in Auto components, leveraging Artificial Intelligence and Machine Learning (AI/ML) technologies. The proposed system automates the fracture analysis process, enhancing speed, reliability, and accessibility for users with varying levels of expertise. The platform enables users to upload images of fractured parts, which are then processed by an AI/ML engine. The engine employs an image classification model to identify the type of fracture and a segmentation model to detect and analyze the direction of the fracture. The segmentation model accurately predicts cracks in the images, providing detailed insights into the direction and progression of the fractures. Additionally, the solution offers an intuitive interface for stakeholders to review past analyses and upload new images for examination. The AI/ML engine further examines the origin of the fracture, its progression pattern, and the
Aerospace and defense system designers are demanding scalable and high-performance I/O solutions. While traditional mezzanine standards have proven reliable, they often fall short of meeting modern bandwidth, size, and flexibility requirements. This challenge is particularly evident in aerospace and defense applications where high-speed data processing must align with stringent size, weight, and power (SWaP) constraints.
Unmanned Underwater Vehicles (UUVs) are used around the world to conduct difficult environmental, remote, oceanic, defense and rescue missions in often unpredictable and harsh conditions. A new study led by Flinders University and French researchers has now used a novel bio-inspired computing artificial intelligence solution to improve the potential of UUVs and other adaptive control systems to operate more reliability in rough seas and other unpredictable conditions.
In a world grappling with a multitude of health threats — ranging from fast-spreading viruses to chronic diseases and drug-resistant bacteria — the need for quick, reliable, and easy-to-use home diagnostic tests has never been greater. Imagine a future where these tests can be done anywhere, by anyone, using a device as small and portable as your smartwatch. To do that, you need microchips capable of detecting minuscule concentrations of viruses or bacteria in the air.
Speed and flexibility are increasingly becoming the cornerstones of modern manufacturing, even as their continued adoption must align with existing values of cost and reliability all while keeping up with the demands for smarter, more complex products. This presents many challenges to machine builders since they must keep pace with the complexity of upcoming products while also being ready to meet the demands of the companies that will buy and operate these machines when it comes to efficiency, rapid production line ramp up, small batch sizes and high quality. Artificial intelligence will be a key tool going forward in achieving these results, offering the ability to more rapidly design, prototype, and implement changes and solutions through superior data analytics abilities and improved human-machine interactions.
Traditional vehicle diagnostics often rely on manual inspections and diagnostic tools, which can be time-consuming, inconsistent, and prone to human error. As vehicle technology evolves, there is a growing need for more efficient and reliable diagnostic methods. This paper introduces an innovative AI-based diagnostic system utilizing Artificial Intelligence (AI) to provide expert-level analysis and solutions for automotive issues. By inputting various details such as the vehicle’s make, model, year, mileage, problem description, and symptoms, the AI system generates comprehensive diagnostics, identifies potential causes, suggests step-by-step repair solutions, and offers maintenance tips. The proposed system aims to enhance diagnostic accuracy and efficiency, ultimately benefiting mechanics and vehicle owners. The system’s effectiveness is evaluated through various experiments and case studies, showcasing its potential to revolutionize vehicle diagnostics.
Researchers have developed a new method for predicting what data wireless computing users will need before they need it, making wireless networks faster and more reliable. The new method makes use of a technique called a “digital twin,” which effectively clones the network it is supporting.
This SAE Standard for reliability-centered maintenance (RCM) is intended for use by any organization that has or makes use of physical assets or systems that it wishes to manage responsibly.
Just as a business needs an effective and reliable service to deliver its goods to customers, medications need an effective delivery system to get them to the specific area of the body where they can have an impact.
Advances in IoT and electronic technology are enabling more personalized, continuous medical care. People with medical conditions that require a high degree of monitoring and continuous medication infusion can now take advantage of wearable medicine injection devices to treat their problems. Wireless communication allows medical personnel to monitor and adjust the amount and flow rate of an individual’s medication. The small size of the injectors enables the individual to be active and not be burdened or limited by a line-powered instrument (see Figure 1).
As the U.S. military embraces vehicle electrification, high-reliability components are rising to the occasion to support their advanced electrical power systems. In recent years, electronic device designers have started using wide band-gap (WBG) materials like silicon carbide (SiC) and gallium nitride (GaN) to develop the semiconductors required for military device power supplies. These materials can operate at much higher voltages, perform switching at higher frequencies, and feature better thermal characteristics. Compared to silicon, SiC-based semiconductors provide superior performance. The growing availability of these materials, in terms of access and cost, continues to encourage electrification. With the ever-present pressure of size, weight, and power (SWaP) optimization in military applications, and a desire to keep up with the pace of innovation, there's a need for capacitors that can deliver higher power efficiency, switching frequency, and temperature resistance under harsh
American drivers have long been accustomed to quickly filling up at a gas station with plenty of fuel available, and electric vehicle drivers want their pit stops to mimic this experience. Driver uncertainty about access to charging during long trips remains a barrier to broader EV adoption, even as the U.S. strives to combat climate change by converting more drivers.
As aerospace engineers push the boundaries of new frontiers, the need for advanced materials that can withstand the rigorous demands of these advanced applications is relentless. These materials go beyond functionality; it is about ensuring reliability in the skies, where failure is not an option. Fluorosilicone can help do exactly that. In the 1960s, the U.S. Air Force noticed that conventional silicone-based sealants, coatings, and other components degraded rapidly when exposed to fuels, de-icing fluids, and other hydrocarbon-based solvents. Dimethyl-based silicones are non-polar and easily absorb hydrocarbon-based solvents, which may result in material swelling, mechanical weakening, and ultimately, failure.
For many patients waiting for a donor heart, the only way to live a decent life is with the help of a pump attached directly to their heart. This pump requires about as much power as a TV, which it draws from an external battery via a seven-millimeter-thick cable. The system is handy and reliable, but it has one big flaw: despite medical treatment, the point at which the cable exits the abdomen can be breached by bacteria.
Though modal analysis is a common tool to evaluate the dynamic properties of a structure, there are still many individual decisions to be made during the process which are often based on experience and make it difficult for occasional users to gain reliable and correct results. One of those experience-based choices is the correct number and placement of reference points. This decision is especially important, because it must be made right in the beginning of the process and a wrong choice is only noticeable by chance in the very end of the process. Picking the wrong reference points could result in incomplete modal analysis outcomes, as it might make certain modes undetectable, compounded by the user's lack of awareness about these missing modes. In the paper an innovative approach will be presented to choose the minimal number of mandatory reference points and their placement. While other approaches use results of numerical simulations or rely on a visual evaluation of measurement
The standard may have changed everything, just not how you think. On May 25, 2023, Ford made an announcement that seemed unimaginable. For those in the EV and standards industry, it caught many by surprise. Ford was partnering with Tesla to move away from the CCS (J1772/CCS) standard that's on a majority of electric vehicles and would switch to the Tesla NACS (North American Charging Standard) in the future. “When the J3400 news broke or the NACS partnerships broke, it kind of went around the regulatory ‘there's no way around that’ and it was just the worst day because I thought we were going to lose, open, collaboratively created standards,” Sarah Hipel, standards and reliability program manager for the Joint Office of Energy and Transportation told the audience at SAE's WCX 2024. Hipel was on a panel titled, “In The Wake of J3400 (NACS), Are Standards Still Needed?”
In commercial aerospace, the application areas for motors are wide and varied, each with their own unique requirements. From electric vehicle take-off and landing (eVTOL) air taxis to business jets to long-haul commercial transport aircraft, DC motors must endure various environmental conditions like extreme temperatures, shock and vibration, atmospheric pressures and signal interference, to name just a few. These applications may also demand motors that provide a fast response, high power or torque density. In addition to these requirements, the aerospace industry perpetually calls for lightweight materials and smaller installation spaces. Taken together, it can be very difficult to specify and buy a reliable motor for mission-critical equipment. This article will present common commercial aerospace applications that pose performance and environmental challenges for DC motors along with a summary of the stringent aerospace industry standards that the motors must satisfy. It will also
General Motors (GM) is working towards a future world of zero crashes, zero emissions and zero congestion. It’s “Ultium” platform has revolutionized electric vehicle drive units to provide versatile yet thrilling driving experience to the customers. Three variants of traction power inverter modules (TPIMs) including a dual channel inverter configuration are designed in collaboration with LG Magna e-Powertrain (LGM). These TPIMs are integrated with other power electronics components inside Integrated power electronics (IPE) to eliminate redundant high voltage connections and increase power density. The developed power module from LGM has used state-of-the art sintering technology and double-sided cooled structure to achieve industry leading performance and reliability. All the components are engineered with high level of integration skills to utilize across TPIM variants. Each component in the design is rigorously analyzed and tested from component to system levels to ensure high
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