Estimation of lithium-ion battery discharge capacity by integrating optimized explainable-AI and stacked LSTM model
Accurate lithium-ion battery state of health evaluation is crucial for correctly operating and
managing battery-based energy storage systems. Experimental determination is problematic …
managing battery-based energy storage systems. Experimental determination is problematic …
Tool wear prediction in face milling of stainless steel using singular generative adversarial network and LSTM deep learning models
During milling operations, wear of cutting tool is inevitable; therefore, tool condition
monitoring is essential. One of the difficulties in detecting the state of milling tools is that they …
monitoring is essential. One of the difficulties in detecting the state of milling tools is that they …
A novel approach of tool condition monitoring in sustainable machining of Ni alloy with transfer learning models
Cutting tool condition is crucial in metal cutting. In-process tool failures significantly
influences the surface roughness, power consumption, and process endurance. Industries …
influences the surface roughness, power consumption, and process endurance. Industries …
[HTML][HTML] Machining parameter optimization and experimental investigations of nano-graphene mixed electrical discharge machining of nitinol shape memory alloy
Excellent characteristics of Nitinol shape memory alloys (SMAs) makes them favourable for
use in industrial applications. Precision machining of such advanced alloys becomes a key …
use in industrial applications. Precision machining of such advanced alloys becomes a key …
[HTML][HTML] An efficient IoT-Artificial intelligence-based disease prediction using lightweight CNN in healthcare system
AA Malibari - Measurement: Sensors, 2023 - Elsevier
In recent years, chronic disease (heart or kidney disease) is a leading cause of death
worldwide. Chronic disease prediction is a very complicated task. Doctors who are …
worldwide. Chronic disease prediction is a very complicated task. Doctors who are …
Enhancing tool wear prediction accuracy using Walsh–Hadamard transform, DCGAN and dragonfly algorithm-based feature selection
Tool wear is an important concern in the manufacturing sector that leads to quality loss,
lower productivity, and increased downtime. In recent years, there has been a rise in the …
lower productivity, and increased downtime. In recent years, there has been a rise in the …
Exploring the application sphere of electrical discharge machining in composite materials considering surface features: a content analysis
The quantitative content analysis focuses on identifying and quantifying, whereas the
qualitative approach focuses on analyzing and comprehending. It examines words, ideas …
qualitative approach focuses on analyzing and comprehending. It examines words, ideas …
Effect of Multi-walled carbon nanotubes on the performance evaluation of Nickel-based super-alloy–Udimet 720 machined using WEDM process
The diverse capabilities of nickel-based super-alloy (Udimet 720), like robust mechanical
strength, ductility, resistance to excessive temperature deformation, and advanced corrosion …
strength, ductility, resistance to excessive temperature deformation, and advanced corrosion …
Multi-Response Optimization of Al2O3 Nanopowder-Mixed Wire Electrical Discharge Machining Process Parameters of Nitinol Shape Memory Alloy
Shape memory alloy (SMA), particularly those having a nickel–titanium combination, can
memorize and regain original shape after heating. The superior properties of these alloys …
memorize and regain original shape after heating. The superior properties of these alloys …
Balanced k-star: An explainable machine learning method for internet-of-things-enabled predictive maintenance in manufacturing
B Ghasemkhani, O Aktas, D Birant - Machines, 2023 - mdpi.com
Predictive maintenance (PdM) combines the Internet of Things (IoT) technologies with
machine learning (ML) to predict probable failures, which leads to the necessity of …
machine learning (ML) to predict probable failures, which leads to the necessity of …