Browse Topic: Data exchange
Electrochemical machining (ECM) is a highly efficient method for creating intricate structures in materials that conduct electricity, regardless of their level of hardness. Due to the growing demand for superior products and the necessity for quick design changes, decision-making in the manufacturing industry has become increasingly intricate. The preliminary intention of this work is to concentrate on Cupronickel and suggest the creation of an Adaptive Neuro-Fuzzy Inference System (ANFIS) model for the purpose of predictive modeling in ECM. The study employs a Taguchi-grey relational analysis (GRA) methodology to attain multi-objective optimization, with the target of maximizing material removal rate, minimizing surface roughness, and simultaneously achieving precise geometric tolerances. The ANFIS model suggested for Cupronickel provides more flexibility, efficiency, and accuracy compared to conventional approaches, allowing for enhanced monitoring and control in ECM operations
Electrochemical machining (ECM) is a highly efficient method for creating intricate structures in materials that conduct electricity, irrespective of their hardness. Due to the increasing demand for superior products and the necessity for quick design modifications, decision-making in the manufacturing sector has become progressively more difficult. This study focuses on Cupronickel and suggests creating predictive models to anticipate performance metrics in ECM through regression analysis. The experiments are formulated based on Taguchi's principles, and a multiple regression model is utilized to deduce the mathematical equations. The Taguchi approach is employed for single-objective optimization to ascertain the ideal combination of process parameters for optimizing the material removal rate. The proposed prediction technique for Cupronickel is more adaptable, efficient, and accurate in comparison to current models, providing enhanced monitoring capabilities. The updated models have
The intention of this exploration is to evolve an optimization method for the Electrochemical Machining (ECM) process on Haste alloy material, taking into account various performance characteristics. The optimization relies on the amalgamation of the Taguchi method with an Adaptive Neuro-Fuzzy Inference System (ANFIS). Haste alloy is extensively utilized in the aerospace, nuclear, marine, and car sectors, specifically in situations that are prone to corrosion. The experimental trials are organized based on Taguchi's principles and involve three machining variables: feed rate, electrolyte flow rate, and electrolyte concentration. This examination examines performance indicators, including the pace at which material is removed and the roughness of the surface. It also includes geometric factors such as overcut, shape, and tolerance for orientation. The results suggest that the rate at which the feed is supplied is the most influential element affecting the necessary performance standards
The aim of this study is to create an Adaptive Neuro-Fuzzy Inference System (ANFIS) model for the Electrochemical Machining (ECM) process using Nimonic Alloy material, with a specific focus on several performance aspects. The optimization strategy utilizes the combination of the Taguchi method and ANFIS integration. Nimonic Alloy is widely employed in the aerospace, nuclear, marine, and car sectors, especially in situations that are susceptible to corrosion. The experimental trials are designed according to Taguchi's method and involve three machining variables: feed rate, electrolyte flow rate, and electrolyte concentration. This study investigates performance indicators, such as the rate at which material is removed, the roughness of the surface, and geometric characteristics, including overcut, shape, and tolerance for orientation. Based on the analysis, it has been determined that the feed rate is the main component that influences the intended performance criteria. In order to
The objective of this research is to develop an optimization strategy for the Electrochemical Drilling process on Nimonic alloy material, taking into account various performance factors. The optimization strategy relies on the integration of the Taguchi method with Grey Relational Analysis (GRA). Nimonic is extensively utilized in aerospace, nuclear, and marine industries, specifically in situations that are prone to corrosion. The experimental trials are structured based on Taguchi's principle and encompass three machining variables: feed rate, electrolyte flow rate, and electrolyte concentration. This inquiry examines performance indicators like the rate of material removal, surface roughness, as well as geometric parameters such as overcut, shape, and orientation tolerance. Based on the investigation, it is determined that the feed rate is the primary factor that directly affects the intended performance criteria. In order to enhance the accuracy of predictions, multiple regression
The aspiration of this exploration is to evolve an optimization technique for the Electrochemical Drilling process on Haste alloy material, considering various performance factors. The Taguchi approach, along with Grey Relational Analysis (GRA), forms the basis for optimization. Haste alloy has a wider range of uses in industries such as aerospace, nuclear, and marine, especially in harsh environments. The experimental trials conducted in accordance with Taguchi's approach have utilized three machining variables: feed rate, electrolyte flow rate, and electrolyte concentration. When doing this examination, we analyze not only the rate at which material is removed and the roughness of the surface, but also other characteristics that indicate performance, such as overcut, shape, and orientation tolerance. The analytical findings indicate that the feed rate is the primary factor that directly impacts the required performance standards. Regression models are constructed to make predictions
A 20-cell self-humidifying fuel cell stack containing two types of MEAs was assembled and aged by a 1000-hour durability test. To rapidly and effectively analyze the primary degradation, the polarization change curve is introduced. As the different failure modes have a unique spectrum in the polarization change curve, it can be regarded as the fingerprint of a special degradation mode for repaid analysis. By means of this method, the main failure mode of two-type MEAs was clearly distinguished: one was attributed to the pinhole formation at the hydrogen outlet, and another was caused by catalyst degradation only, as verified by infrared imaging. The two distinct degradation phases were also classified: (i)conditioning phase, featuring with high decay rate, caused by repaid ECSA change from particle size growth of catalyst. (ii) performance phase with minor voltage loss at long test duration, but with RH cycling behind, as in MEA1. Then, an effective H2-pumping recovery is conducted
The term Software-Defined Vehicle (SDV) describes the vision of software-driven automotive development, where new features, such as improved autonomous driving, are added through software updates. Groups like SOAFEE advocate cloud-native approaches – i.e., service-oriented architectures and distributed workloads – in vehicles. However, monitoring and diagnosing such vehicle architectures remain largely unaddressed. ASAM’s SOVD API (ISO 17978) fills this gap by providing a foundation for diagnosing vehicles with service-oriented architectures and connected vehicles based on high-performance computing units (HPCs). For service-oriented architectures, aspects like the execution environment, service orchestration, functionalities, dependencies, and execution times must be diagnosable. Since SDVs depend on cloud services, diagnostic functionality must extend beyond the vehicle to include the cloud for identifying the root cause of a malfunction. Due to SDVs’ dynamic nature, vehicle systems
The properties of organic nitrate ester that inhibit scale formation were investigated in order to acquire a better understanding of ferrous carbide precipitation from supersaturated solutions. When the scale inhibitor was present, precipitation rates were much lower than when it was missing, even at very low concentrations. When the temperature and time are increased simultaneously, more scale is deposited. The effect of nitrate ester on scale deposition demonstrates that the inhibitory dosage is relatively low at low temperatures but rapidly increases when exposed to high temperatures. The inhibitor is thought to alter the shape of the first crystals by binding to dynamic growth sites and inhibiting the threshold level of development.
Radiation has garnered the most attention in the research that has been conducted on polyethylene sheets. According to the calculations, there were 145892.35 kGy in total radiation doses administered. An ultraviolet visible spectrophotometer was used to examine the impact that electron beam irradiation had on the optical constants. Two of the most crucial variables taken into account when calculating the optical constants and the absorption coefficient are the reflectance and transmittance of polyurethane sheets. Reduced light transmission through the sheet achieves these characteristics, which are related to the transmittance and reflectance of the Fresnel interface. Cross linking makes it more challenging for the polyurethane molecular chains to become fixed. Both the refractive index and the dispersion properties have been altered as a direct result of this. Despite the fact that the doses of electron irradiation were getting lower, it eventually rose to 105 kGy. Contrary to the
Today's battery management systems include cloud-based predictive analytics technologies. When the first data is sent to the cloud, battery digital twin models begin to run. This allows for the prediction of critical parameters such as state of charge (SOC), state of health (SOH), remaining useful life (RUL), and the possibility of thermal runaway events. The battery and the automobile are dynamic systems that must be monitored in real time. However, relying only on cloud-based computations adds significant latency to time-sensitive procedures such as thermal runaway monitoring. Because automobiles operate in various areas throughout the intended path of travel, internet connectivity varies, resulting in a delay in data delivery to the cloud. As a result, the inherent lag in data transfer between the cloud and cars challenges the present deployment of cloud-based real-time monitoring solutions. This study proposes applying a thermal runaway model on edge devices as a strategy to reduce
Gear shifting effort or force especially in manual transmission has been one of the key factors for subjective assessment in passenger vehicle segment. An optimum effort to shift into the gears creates a big difference in overall assessment of the vehicle. The gear shifting effort travels through the transmission shifting system that helps driver to shift between the different available gears as per the torque and speed demand. The shifting system is further divided into two sub-systems. 1. Peripheral system [Gear Shift Lever with knob and shift Cable Assembly] and Shift system inside the transmission [Shift Tower Assembly, Shift Forks, Hub and sleeve Assembly with keys, Gear Cones and Synchronizer Rings etc.] [1]. Both the systems have their own role in overall gear shifting effort. There has been work already done on evaluation of the transmission shifting system as whole for gear shifting effort with typical test bench layouts. Also, work has been on assessment of life of the
Chinese battery manufacturer CATL (Contemporary Amperex Technology Co. Ltd.) completed the launch of its TECTRANS battery system for the commercial transport sector at IAA Transportation, which took place in September in Hanover, Germany. CATL added its heavy-duty truck and bus/coach battery ranges to the light-truck range that the company launched in China in July 2024. For heavy-duty trucks, CATL offers two alternatives: the TECTRANS - T Superfast Charging Edition and the TECTRANS - T Long Life Edition. As the name suggests, the Superfast Charging Edition is designed to offer rapid charging capability for operators needing to recharge during a duty cycle. CATL quotes a 4C peak charging rate, which would permit a charge to 70% in 15 minutes.
Researchers have achieved data rates as high as 424Gbit/s across a 53-km turbulent free-space optical link using plasmonic modulators — devices that uses special light waves called surface plasmon polaritons to control and change optical signals. The new research lays the groundwork for high-speed optical communication links that transmit data over open air or space.
Imagine you had a dedicated wireless channel for communication that was hundreds of times faster than the Wi-Fi we use today, with hundreds of times more bandwidth. That dream may not be far off thanks to the development of metasurfaces: tiny engineered sheets that can reflect and otherwise direct light in desired ways.
The global medical device market is projected to reach a value of $656 billion USD by 2032 with a CAGR of 3 percent over the coming decade.1 The preceding decades of globalization and increased prosperity has provided advancement in both medical technology and access to advanced medical care for a greater proportion of the world’s population. Further, an aging population in North America, Europe, and parts of Asia will increase the need for healthcare-related services and medical devices in the coming decades. At present, the North America market continues to dominate the industry, accounting for approximately 43 percent of the market’s revenue share; however, markets in the Asia-Pacific region have the highest expected growth rates in the coming decades.1 Growth and innovation in the medical device market will be critical in the years to come.
When a physician injects a patient with medication from a glass vial, they want to know that the drug inside that vial is sterile and stable. That’s where Genesis Packaging Technologies comes in. Genesis Packaging Technologies, formally a division of the West Company, was founded in 1946. Today, Genesis is a one of the leaders in the science and technology of parenteral vial sealing and residual seal force testing.
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