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

Predictive maintenance is a strategy that uses data from equipment sensors and advanced analytics to predict when a machine is likely to fail, ensuring maintenance can be performed proactively to prevent breakdowns. This enables industries to reduce unexpected failures, improve operational efficiency, and extend the lifespan of critical equipment. It is applicable across a wide range of components, including motors, fans, gearboxes, bearings, conveyors, actuators, and more.

In this post, we demonstrate how to implement a predictive maintenance solution using Foundation Models (FMs) on Amazon Bedrock, with a case study of Amazon’s manufacturing equipment within their fulfillment centers. The solution is highly adaptable and can be customized for other industries, including oil and gas, logistics, manufacturing, and healthcare.

Predictive maintenance overview

Predictive maintenance can be broken down into two key phases: sensor alarm generation and root cause diagnosis. Together, these phases form a comprehensive approach to predictive maintenance, enabling ...