Build a multimodal generative AI assistant for root cause diagnosis in predictive maintenance using Amazon Bedrock

This article demonstrates building a multimodal generative AI assistant for predictive maintenance root cause diagnosis using Amazon Bedrock, with a case study from Amazon fulfillment centers.

• Predictive maintenance combines sensor alarm generation and root cause diagnosis phases
• Over 50% of work orders remain "undetermined" in root cause, creating operational inefficiency
• Assistant analyzes time series sensor data with ISO vibration standards for equipment health classification
• Guided multi-turn conversations retain context for targeted troubleshooting recommendations
• Multimodal inputs support images, audio, and video for comprehensive equipment diagnostics
• Amazon Transcribe converts audio recordings to text for hands-free technician interaction
• Video processing extracts frames and audio for frame-by-frame analysis and captions
• Multimodal RAG retrieves both text and images from repair manuals using reciprocal rank fusion
• Amazon Bedrock Guardrails ensure safety, accuracy, and compliance throughout diagnostics
• Solution reduces downtime and improves operational efficiency across manufacturing, logistics, healthcare

This solution transforms predictive maintenance by providing technicians with AI-powered guidance, significantly reducing undetermined root causes and equipment downtime through intelligent, context-aware troubleshooting.