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About

Dr. Satish Kumar is a young researcher and a keen academician. He is captivated by technology oriented innovative concepts and always looks ahead to execute interdisciplinary projects. He has his expertise in application of Artificial Intelligence into a variety of crucial manufacturing processes, including quality enhancement, process improvement, and optimization. He is now working on several industrial 4.0 initiatives, including digital twin smart manufacturing, remaining usable life estimation, and others. He has authored more than 30 Scopus/WoS indexed international/national journal and conferences publications. He has recently published a patent on “Micro-oxidation Coating device”. He is also currently editing Taylor & Francis CRC Pressbook titled "Industry 4.0 in Small and Medium-Sized Enterprises (SMEs): Opportunities, Challenges, and Solutions." He has completed various research funded proposals at Symbiosis International Deemed University and is also currently working on two research proposals “Inferring quality and fault localization of 3D printer products using Digital twin” and “Artificial Intelligence-based fault detection in bearing using vibration and sound sensor”. One student was recently awarded PhD. under his supervision and is currently guiding 5 Ph.D. research scholars. Dr. Satish Kumar is a young researcher and a keen academician. He is captivated by technology-oriented innovative concepts and always looks ahead to execute interdisciplinary projects. He has expertise in application of Artificial Intelligence into a variety of crucial manufacturing processes, including quality enhancement, process improvement, and optimization. He is now working on several industrial 4.0 initiatives, including digital twin smart manufacturing, remaining usable life estimation, and others. He has authored more than 30 Scopus/WoS indexed international/national journal and conferences publications. He has recently published a patent on “Micro-Oxidation Coating device”. He is also currently editing Taylor & Francis's CRC Pressbook titled "Industry 4.0 in Small and Medium-Sized Enterprises (SMEs): Opportunities, Challenges, and Solutions." He has completed various research funded proposals at Symbiosis International Deemed University and is also currently working on two research proposals “Inferring quality and fault localization of 3D printer products using Digital twin” and “Artificial Intelligence-based fault detection in bearing using vibration and sound sensor”. One student was recently awarded a Ph.D under his supervision and is currently guiding 5 Ph.D research scholars.

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Publication

  • dott image August, 2023

Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach : A review of two decades of research

Industry 4.0 is an era of smart manufacturing. Manufacturing is impossible without the use of machinery. The majority of these machines comprise rotating components and are called rotating m...

  • dott image September, 2022

Explainable AI for Bearing Fault Prognosis Using Deep Learning Techniques

Predicting bearing failures is a vital component of machine health monitoring since bearings are essential parts of rotary machines, particularly large motor machines. In addition, determini...

  • dott image July, 2022

Tool wear prediction using long short-term memory variants and hybrid feature selection techniques

Tool wear prediction is a challenging aspect of the milling machine as the cutting tool is responsible for the accuracy and precision of the final machined product. The accuracy of tool wear...

  • dott image January, 2022

Performance evaluation for tool wear prediction based on Bi-directional, Encoder–Decoder and Hybrid Long Short-Term Memory models

Purpose Excessive tool wear is responsible for damage or breakage of the tool, workpiece, or machining center. Thus, it is crucial to examine tool conditions during the machining process to...

  • dott image September, 2021

Sustainable Development of Smart Manufacturing Driven by the Digital Twin Framework: A Statistical Analysis

The Fourth Industrial Revolution drives industries from traditional manufacturing to the smart manufacturing approach. In this transformation, existing equipment, processes, or devices are r...

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S9-012025-1308238

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