Executive Summary
This paper proposes a five-layer AI-based predictive maintenance (PdM) framework for the Indian Armed Forces, addressing unique challenges like legacy systems and diverse operating environments. The framework covers sensor acquisition, edge processing, secure communication, central AI analytics, and decision support to enhance operational readiness. It aims to improve equipment reliability and reduce maintenance costs through proactive failure prediction.
Why It Matters
This document is crucial for defense analysts as it outlines a strategic framework for integrating AI-driven predictive maintenance into the Indian military, directly impacting operational readiness and defense capabilities. It highlights India's efforts to indigenize defense technology and reduce reliance on foreign suppliers.
Key Takeaways
- The Indian Armed Forces face unique challenges in integrating AI and autonomous systems for predictive maintenance, including legacy systems, resource constraints, and diverse operating environments.
Source evidence · PDF page 1
This paper examines the impact of AI-enabled autonomous systems in military operations with a focus on the specific needs of the Indian Armed Forces. Through a structured literature review, unique challenges such as legacy systems integration, resource constraints, and multi-domain operations are identified.
- A five-layer AI-based predictive maintenance framework is proposed for the Indian military, encompassing sensor acquisition, edge processing, secure communication, central AI analytics, and decision support.
Source evidence · PDF page 1
A tailored five-layer Predictive maintenance framework aligned to Indian defence requirements is proposed, covering sensor acquisition, edge processing, secure communication, central AI analytics, and decision support. The framework addresses data quality, algorithm robustness, cybersecurity, and human-machine collaboration.
- The future of predictive maintenance in the Indian military is promising, with increasing sensor deployment and data availability expected to enhance model accuracy and reliability, supported by advancements like explainable AI and digital twins.
Source evidence · PDF page 8
The future of predictive maintenance in the Indian Military is very promising, especially as more sensors and digital systems are gradually fitted on equipment such as armoured vehicles, aircraft, naval platforms and unmanned systems. As more operational data from these platforms becomes available, predictive maintenance models will become more accurate and reliable.
Strategic Relevance
The proposed AI-based predictive maintenance framework directly enhances the operational readiness and sustainability of the Indian military's diverse equipment fleet. By reducing downtime and optimizing resource utilization, it contributes to national security and supports India's strategic goals of indigenization and self-reliance in defense technology.