<p>Health & Usage Monitoring System (HUMS), a generic component in aircraft maintenance, is getting an indigenous AI thrust in India. The Defence Research and Development Organisation (DRDO) has worked with Hyderabad-based Smart Machines and Structures (SMS) in the development of a HUMS platform that applies Machine Learning to forecast flight failures.</p>.<p>SMS has developed the system for MiG-29K, the Indian Navy’s carrier-based fighter. The solution uses ML and data analytics to process data from the flight data recorder and helps the Navy improve the aircraft’s serviceability and combat readiness.</p>.<p><strong>Also Read: <a href="https://www.deccanherald.com/national/us-promises-to-fast-track-clearance-to-ge-to-make-jet-engines-in-india-for-hal-s-combat-aircraft-1186811.html" target="_blank">US promises to fast-track clearance to GE to make jet engines in India for HAL’s combat aircraft</a></strong></p>.<p>Srinivas Aluri, founder of SMS, said the solution works as an “early warning” system. “The Navy could run the flight data through our solution and identify components that are susceptible to failure, and a timeline for these failures. The predictions help in scheduling the maintenance,” Aluri told <em>DH</em>. The Navy will analyse the results obtained to address issues related to the engines and airframe. The system has completed preliminary trials.</p>.<p>Aluri said the solution is capable of automating most of the existing checks that track various pre-flight parameters of the aircraft, effectively saving 10 to 15 minutes on a flight. He said the technology was being exclusively integrated with the MiG 29Ks but it could be transferred to other aircraft.</p>.<p>On Tuesday, Defence Minister Rajnath Singh handed over the system to Vice Chief of the Naval Staff Admiral Satish Namdeo Ghormade, on the sidelines of Aero India 2023.</p>.<p>Suryanarayana Raju Pakalapati, head of engineering and AI, SMS, said while existing flight data recorders worked as diagnostic tools that help to make the corrections based on post-flight readings, predictive maintenance facilitated “minor indications” of failures in the making. The company’s work, under the guidance of DRDO scientists, involved extensive processing of data from Navy aircraft.</p>.<p>SMS pitched for the project in response to a problem statement on predictive maintenance issued by the Navy, in 2018. The project was conceived under DRDO’s Technology Development Fund (TDF) which extends financial support and expertise to upgrade existing systems in line with a larger Make in India vision. Of the Rs-1.7 crore fund allocated for the HUMS, 90% was provided under TDF.</p>
<p>Health & Usage Monitoring System (HUMS), a generic component in aircraft maintenance, is getting an indigenous AI thrust in India. The Defence Research and Development Organisation (DRDO) has worked with Hyderabad-based Smart Machines and Structures (SMS) in the development of a HUMS platform that applies Machine Learning to forecast flight failures.</p>.<p>SMS has developed the system for MiG-29K, the Indian Navy’s carrier-based fighter. The solution uses ML and data analytics to process data from the flight data recorder and helps the Navy improve the aircraft’s serviceability and combat readiness.</p>.<p><strong>Also Read: <a href="https://www.deccanherald.com/national/us-promises-to-fast-track-clearance-to-ge-to-make-jet-engines-in-india-for-hal-s-combat-aircraft-1186811.html" target="_blank">US promises to fast-track clearance to GE to make jet engines in India for HAL’s combat aircraft</a></strong></p>.<p>Srinivas Aluri, founder of SMS, said the solution works as an “early warning” system. “The Navy could run the flight data through our solution and identify components that are susceptible to failure, and a timeline for these failures. The predictions help in scheduling the maintenance,” Aluri told <em>DH</em>. The Navy will analyse the results obtained to address issues related to the engines and airframe. The system has completed preliminary trials.</p>.<p>Aluri said the solution is capable of automating most of the existing checks that track various pre-flight parameters of the aircraft, effectively saving 10 to 15 minutes on a flight. He said the technology was being exclusively integrated with the MiG 29Ks but it could be transferred to other aircraft.</p>.<p>On Tuesday, Defence Minister Rajnath Singh handed over the system to Vice Chief of the Naval Staff Admiral Satish Namdeo Ghormade, on the sidelines of Aero India 2023.</p>.<p>Suryanarayana Raju Pakalapati, head of engineering and AI, SMS, said while existing flight data recorders worked as diagnostic tools that help to make the corrections based on post-flight readings, predictive maintenance facilitated “minor indications” of failures in the making. The company’s work, under the guidance of DRDO scientists, involved extensive processing of data from Navy aircraft.</p>.<p>SMS pitched for the project in response to a problem statement on predictive maintenance issued by the Navy, in 2018. The project was conceived under DRDO’s Technology Development Fund (TDF) which extends financial support and expertise to upgrade existing systems in line with a larger Make in India vision. Of the Rs-1.7 crore fund allocated for the HUMS, 90% was provided under TDF.</p>