Research Papers

Uncover how model-based planning techniques can enhance maintenance reliability by estimating complex asset behaviour from limited operational data.

Explore how principles of context-aware AI from recent cognitive flow research can enhance maintenance decision support and accelerate fault diagnosis on the shop floor.

Dive into a unified framework and roadmap for context-aware AI in maintenance, bridging academic research with practical applications to drive manufacturing reliability.

Explore how cutting-edge statistical methods for AI reliability can enhance maintenance decision support and ensure trustworthy outcomes on the shop floor.

Discover how context-aware AI troubleshooting strategies from medical oxygen concentrators can enhance maintenance intelligence and asset reliability in manufacturing using iMaintain’s platform.

Explore how iMaintain combines context-aware augmented reality and AI decision support to empower technicians, accelerate fault resolution, and preserve critical maintenance knowledge.

Explore how retrieval-augmented generation in extended reality with LLMs is revolutionising context-aware maintenance assistance for modern manufacturing teams.

Delve into the latest research on knowledge-based maintenance intelligence and learn how iMaintain captures and structures engineering knowledge to drive reliability and performance.

Dive into how LLM-powered infrastructure can transform maintenance operations by capturing context-aware engineering knowledge for faster troubleshooting and reduced downtime.

Learn how iMaintain’s AI maintenance intelligence supports engineers in driving sustainable operations by reducing waste, extending asset life, and lowering environmental impact.