Chennai, India

Ramaswamy Melatoor Narayanan


Average Co-Inventor Count = 7.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2023

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1 patent (USPTO):Explore Patents

Title: Ramaswamy Melatoor Narayanan: Innovator in Manufacturing Systems

Introduction

Ramaswamy Melatoor Narayanan is a notable inventor based in Chennai, India. He has made significant contributions to the field of manufacturing systems through his innovative use of machine learning technologies. His work focuses on enhancing the efficiency and reliability of manufacturing processes.

Latest Patents

Ramaswamy holds a patent for "Detecting outliers at a manufacturing system using machine learning." This patent describes methods and systems for identifying outliers in a manufacturing environment. The process involves collecting data from sensors during the manufacturing of a first set of substrates. This data is then analyzed using a trained machine learning model to extract drift amounts from target parameter values. The results lead to the assignment of health ratings for both substrates and sensors, which are communicated to a client device connected to the manufacturing system. He has 1 patent to his name.

Career Highlights

Ramaswamy is currently employed at Applied Materials, Inc., a leading company in the field of materials engineering. His role involves leveraging advanced technologies to improve manufacturing processes. His expertise in machine learning has positioned him as a key player in the development of innovative solutions in the industry.

Collaborations

Ramaswamy has collaborated with several talented individuals, including Bharath Ram Sundar and Raman K Nurani. These collaborations have fostered a creative environment that encourages the exchange of ideas and the development of cutting-edge technologies.

Conclusion

Ramaswamy Melatoor Narayanan is a distinguished inventor whose work in machine learning and manufacturing systems has the potential to revolutionize the industry. His contributions are paving the way for more efficient and reliable manufacturing processes.

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