MUMBAI, India, Aug. 31 -- Intellectual Property India has published a patent application (202644098365 A) filed by C Pavani; Dayananda Sagar Academy Of Technology And Management; Sushma H M; Ganesh C R; Dr. Manoj Kumar M; Nagesh Kumar D. N; and Kambam Sireesha on August 14, 2026, for Generative Ai-Integrated Digital Twin For Predictive Maintenance And Decision Support In Smart Manufacturing.
Inventors include C Pavani; Dayananda Sagar Academy Of Technology And; Sushma H M; Ganesh C R; Dr. Manoj Kumar M; Nagesh Kumar D. N; and Kambam Sireesha.
The application for the patent was published on August 28, 2026, under issue no. 35/2026.
Abstract: The present invention relates to a Generative AI-Integrated Digital Twin for Predictive Maintenance and Decision Support in Smart Manufacturing, designed to enable real-time monitoring, failure prediction, operational optimization, and intelligent maintenance planning for industrial equipment. The system integrates Internet of Things (IoT) sensors, Digital Twin technology, machine learning, and Generative Artificial Intelligence (GenAI) to establish a dynamic virtual representation of physical manufacturing assets. Real- time parameters including temperature, vibration, pressure, rotational speed, energy consumption, and equipment operating conditions are continuously acquired from industrial machines and synchronized with the corresponding Digital Twin. A predictive analytics module processes historical and real-time data to identify anomalies, estimate equipment degradation, and predict potential failures and remaining useful life. A Generative AI module analyzes the Digital Twin state and generates possible future operational scenarios, maintenance strategies, and what-if simulations. The generated scenarios are evaluated against equipment constraints and operational conditions before producing actionable recommendations. A decision-support module provides maintenance schedules, failure alerts, optimized operating parameters, and recommended corrective actions through an interactive interface. The system further incorporates a feedback mechanism that updates the Digital Twin using subsequent machine conditions and maintenance outcomes. The proposed invention enables proactive maintenance, reduces unplanned downtime, improves equipment utilization, optimizes maintenance resources, and supports intelligent and reliable decision-making in smart manufacturing environments.
Disclaimer: Curated by HT Syndication.
