A5082854838- Quality and Safety in Healthcare
- Imbalanced Data Classification Techniques
- Explainable Artificial Intelligence (XAI)
- Advanced machining processes and optimization
- Machine Fault Diagnosis Techniques
- Quality and Supply Management
- Infrastructure Maintenance and Monitoring
- Environmental Sustainability in Business
- Reliability and Maintenance Optimization
- High voltage insulation and dielectric phenomena
- Advanced Machining and Optimization Techniques
- Electrical Fault Detection and Protection
- Adversarial Robustness in Machine Learning
- Statistical and Computational Modeling
- Power Transformer Diagnostics and Insulation
- Sustainable Supply Chain Management
- Risk and Safety Analysis
- Anomaly Detection Techniques and Applications
- Modeling, Simulation, and Optimization
- Metal Alloys Wear and Properties
Malaviya National Institute of Technology Jaipur
2022-2024
In the realm of supply chains, necessity a robust reverse logistics network is paramount. While substantial efforts have been directed towards enhancing forward logistics, domain remains underdeveloped. This article presents an approach that centers on formulation for Indian e-commerce company specializing in apparel sales. Through construction single and multi-objective integer programs, aim to simultaneously mitigate economic costs environmental repercussions. To tactfully address concerns...
Implementing predictive maintenance is paramount in guaranteeing the dependability and efficiency of intricate industrial systems. Classification approaches have been extensively utilized to detect anticipate potential malfunctions acknowledged Numerous machine learning algorithms exhibit effectiveness, yet they encounter interpretability issues, posing a challenge comprehending fundamental factors contributing their predictions. This study investigates utilization for classification domain...
<title>Abstract</title> Predictive maintenance helps organizations to reduce equipment downtime, optimize schedules, and enhance operational efficiency. By leveraging machine learning algorithms predict when failure will likely occur, teams can proactively schedule activities prevent unexpected breakdowns. Anomaly detection fault classification are essential components of predictive maintenance. involves analyzing sensor data collected from identify deviations normal behavior. Fault...
Substantial capital investments in vital assets, particularly power transformers, necessitate the application of precise diagnostics. These diagnostics are crucial for assessing performance, identifying potential issues, and ensuring these assets' long-term operational maintenance efficiency. The primary objective is proactively mitigating asset failure risk subsequent need costly replacements. In recent years, significant progress has been made developing AI models fault classification,...