MUMBAI, India, Aug. 24 -- Intellectual Property India has published a patent application (202631085942 A) filed by National Institute Of Technology Jamshedpur on July 14, 2026, for “defect Genome-Driven Self-Healing Laser Powder Bed Fusion Manufacturing System With Federated Artificial Intelligence And Physics- Informed Digital Twin Control”.
Inventors include Saikat Ranjan Maity; Abhijit Dey; and Goutam Sutradhar.
The application for the patent was published on August 21, 2026, under issue no. 34/2026.
Abstract: The present invention relates to a Defect Genome-Driven Self-Healing Laser Powder Bed Fusion (LPBF) Manufacturing System with Federated Artificial Intelligence and Physics-Informed Digital Twin Control for enhancing the reliability, adaptability, and quality of metal additive manufacturing processes. The system comprises an LPBF manufacturing unit, a multi-modal sensor network, a data acquisition and processing unit, a Defect Genome Engine, a Defect Genome Repository, a Physics- Informed Digital Twin module, a Federated Artificial Intelligence engine, an autonomous process control module, and a self-healing manufacturing unit. The Defect Genome Engine generates and maintains structured defect genomes representing defect signatures, process conditions, material characteristics, thermal histories, corrective actions, and manufacturing outcomes. Real-time process data acquired from multiple sensors are analyzed to identify defect precursors and predict potential anomalies before their occurrence. The Physics-Informed Digital Twin module continuously simulates manufacturing behavior and evaluates process responses, while the Federated Artificial Intelligence engine enables collaborative learning across multiple distributed LPBF systems without sharing sensitive manufacturing data. Based on defect predictions and digital twin simulations, the autonomous process control module dynamically adjusts process parameters including laser power, scan speed, hatch spacing, scan strategy, and layer characteristics to prevent, mitigate, or correct defects during fabrication. The self-healing architecture establishes a closed- loop manufacturing environment capable of continuous learning, adaptive decision-making, predictive defect prevention, and autonomous process optimization. The invention improves component quality, reduces material waste and production downtime, enhances manufacturing efficiency, and enables intelligent next-generation additive manufacturing for aerospace, biomedical, automotive, defense, and industrial applications.
Disclaimer: Curated by HT Syndication.
