Amazon Web Services, Inc. (AWS) announced the general availability of Amazon Lookout for Equipment, a service that uses AWS-developed machine learning models to help customers perform predictive maintenance on the equipment in their facilities. Amazon Lookout for Equipment ingests sensor data from a customer’s industrial equipment (e.g. pressure, flow rate, RPMs, temperature, and power), and then it trains a unique machine-learning model to predict early warning signs of machine failure or suboptimal performance using real-time data streams from the customer’s equipment, per its maker. With Amazon Lookout for Equipment, customers can detect equipment abnormalities with speed and precision, quickly diagnose issues, reduce false alerts, and avoid expensive downtime by taking action before machine failures occur, notes Amazon. To get started, customers upload their sensor data (e.g. pressure, flow rate, RPMs, temperature, and power) to Amazon Simple Storage Service (S3) and provide the relevant S3 bucket location to Amazon Lookout for Equipment. The service will automatically analyze the data, assess normal or healthy patterns, and build a machine-learning model that is tailored to the customer’s environment, claims Amazon. Amazon Lookout for Equipment will then use the custom-built machine learning model to analyze incoming sensor data and identify early warning signs of machine failure or malfunction. For each alert, the service will specify which sensors are indicating an issue and measure the magnitude of its impact on the detected event.
With the continued growth and evolution of Advanced Manufacturing International, Inc. (AMI), the