Pune, India

Ashish Patil

USPTO Granted Patents = 4 

 

Average Co-Inventor Count = 5.6

ph-index = 1

Forward Citations = 4(Granted Patents)


Company Filing History:


Years Active: 2012-2025

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4 patents (USPTO):Explore Patents

Title: Innovations by Ashish Patil in Industrial Process Automation

Introduction

Ashish Patil is a notable inventor based in Pune, India, recognized for his contributions to industrial process automation. With a total of four patents to his name, he has made significant strides in utilizing machine learning and automation technologies to enhance engineering processes.

Latest Patents

Among his latest patents is a system for the automatic extraction of asset data from engineering data sources for generating a Human-Machine Interface (HMI). This innovative system employs machine learning models and algorithms to extract plant assets from engineering diagrams and other data sources. It establishes asset relationships to create a plant asset registry and builds an asset hierarchy, ultimately generating an ontological knowledge base for controlling industrial processes. Another significant patent focuses on the machine learning analysis of piping and instrumentation diagrams (P&IDs). This automated system evaluates and extracts information from P&IDs using machine learning and image processing techniques, improving the accuracy and efficiency of data extraction.

Career Highlights

Ashish has worked with prominent companies such as Schneider Electric Systems USA, Inc. and Geometric Ltd. His experience in these organizations has contributed to his expertise in industrial automation and control systems.

Collaborations

He has collaborated with notable professionals in the field, including Bhaskar Sinha and Sameer Kondejkar, enhancing the impact of his innovations through teamwork and shared knowledge.

Conclusion

Ashish Patil's work in industrial process automation showcases the potential of machine learning and automation technologies in engineering. His patents reflect a commitment to advancing the field and improving operational efficiencies in industrial settings.

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