Browse Topic: Quality, Reliability, and Durability
This SAE Standard provides requirements and guidance to: Develop a Materiel authenticity plan. Procure Materiel from reliable sources. Assure authenticity and conformance of procured Materiel, including methods such as certification, traceability, testing, and inspection appropriate to the Commodity/item in question. Control Materiel identified as counterfeit. Report Suspect or Counterfeit Materiel to other potential users and Authorities Having Jurisdiction.
How engineers can ensure safety, reliability and quality in aerospace systems. Courbevoie, Île-de-France In an industry where failure is not an option and precision is paramount, aerospace manufacturers and suppliers are constantly seeking components and system solutions that deliver trusted reliability, performance, and compliance. Industry standards are a key part of achieving these high expectations, bringing together global leaders in the mobility industries to create defined, repeatable methods and consistent processes. One of these aerospace standards is AS1895 developed by SAE International - a critical standard due to the need for durable components that can withstand extreme conditions and offer high performance: high-temperature resistance, pressure sealing, and long service life with a cost-effective installation method. Leading aerospace companies such as Eaton and Honeywell have been manufacturing components that meet this standard for a long period of time.
This specification covers quality assurance sampling and testing procedures used to determine conformance to applicable specification requirements of carbon and low-alloy steel forgings.
This study introduces a novel Large Language Model (LLM)-driven approach for comprehensive diagnosis and prognostics of vehicle faults, leveraging Diagnostic Trouble Codes (DTCs) in line with industry-standard automation protocols. The proposed model asks for significant advancement in automotive diagnostics by reasoning through the root causes behind the fault codes given by DTC document to enhance fault interpretability and maintenance efficiency, primarily for the technician and in few cases, the vehicle owner. Here LLM is trained on vehicle specific service manuals, sensor datasets, historical fault logs, and Original Equipment Manufacturer (OEM)-specific DTC definitions, which leads to context-aware understanding of the vehicle situation and correlation of incoming faults. Approach validation has been done using field level real-world vehicle dataset for different running scenarios, demonstrating model’s ability to detect complex fault chains and successfully predicting the
In area of modern manufacturing, ensuring product quality and minimizing defects are utmost important for maintaining competitive advantage and customer satisfaction. This paper presents an innovative approach to detect defect by leveraging Artificial Intelligence (AI) models trained using Computer-Aided Design (CAD) data. Traditional defect detection methods often rely on physical inspection, which can be time-consuming and prone to human error. The conventional method of developing an AI model requires a physical part data, By utilizing CAD data, the time to develop an AI model and implementing it to production line station can be saved drastically. This approach involves the use of AI algorithms trained on CAD models to detect and classify defects in real-time. The field trial results demonstrate the effectiveness of this approach in various industrial applications, highlighting its potential to revolutionize defect detection in manufacturing.
This study investigates the phenomenon of receptacle icing during Compressed Natural Gas (CNG) refueling at filling stations, attributing the issue to excessive moisture content in the gas. The research examines the underlying causes, including the Joule-Thomson effect, filter geometries, and their collective impact on flow interruptions. A comprehensive test methodology is proposed to simulate real-world conditions, evaluating various filter types, seal materials and moisture levels to understand their influence on icing and flow cessation. The findings aim to offer ideas for reducing icing problems. This will improve the reliability and safety of CNG refueling systems.
Oil pressure, the most fundamental to engine's performance and longevity, is not only critical to ensure that the engine components are properly lubricated, cooled, and protected against wear and contamination, but also ultimately contributing to reliable engine performance. Due to several factors of engine such as, rotational fluctuation, aeration, functioning of hydraulic components there are fluctuations in oil pressure. In engines, with a crank-mounted fixed displacement oil pump (FDOP), these inherited pressure fluctuations cannot be eliminated completely. However, it is very necessary to control the abnormal oil pressure fluctuation because abnormal pressure fluctuation may lead to malfunction of hydraulic component functioning like variable valve timing (VVT), hydraulic lash adjuster (HLA) and dynamic chain tensioner which can further cause serious issues like excessive or sudden load drops, unstable engine performance, valve train noise, improper valve lift operation etc. In
This paper elucidates the implementation of software-controlled synchronous rectification and dead time configuration for bi-directional controlled DC motors. These motors are extensively utilized in applications such as robotics and automotive systems to prolong their operational lifespan. Synchronous rectification mitigates large current spikes in the H-bridge, reducing conduction losses and improving efficiency [1]. Dead time configuration prevents shoot-through conditions, enhancing motor efficiency and longevity. Experimental results demonstrate significant improvements in motor performance, including reduced thermal stress, decreased power consumption, and increased reliability [2]. The reduction in power consumption helps to minimize thermal stress, thereby enhancing the overall efficiency and longevity of the motor.
Items per page:
50
1 – 50 of 10099