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.
For example, if Amazon Lookout for Equipment detected an issue on a pump with 50 sensors, the service could show which five sensors indicate an issue on a specific motor, and relate that issue to the motor power current and temperature. This allows customers to identify the issue, diagnose the problem, prioritize needed actions, and perform precision maintenance before issues happen—saving them money and improving productivity by preventing down time. Amazon Lookout for Equipment allows customers to get more value from their existing sensors, and it helps them make timely decisions that can materially improve operational efficiency.
In addition to Amazon Lookout for Equipment, AWS offers industrial and manufacturing customers the broadest range of cloud-to-edge industrial machine learning services, including Amazon Monitron (for predictive maintenance using an end-to-end solution comprised of sensors, gateways, and a machine-learning service), Amazon Lookout for Vision (for visual-anomaly detection using computer-vision models in the cloud), and AWS Panorama (for visual inspection using an Appliance and Software Development Kit that brings computer vision models to on-premises cameras).
“Many industrial and manufacturing companies have heavily invested in physical sensors and other technology with the aim of improving the maintenance of their equipment. But even with this gear in place, companies are not in a position to deploy machine learning models on top of the reams of data due to a lack of resources and the scarcity of data scientists. As a result, they miss out on critical insights and actionable findings that would help them better manage their operations,” said Swami Sivasubramanian, VP Amazon Machine Learning, AWS. “Today, we’re excited to announce the general availability of Amazon Lookout for Equipment, a new service that enables customers to benefit from custom machine learning models that are built for their specific environment to quickly and easily identify abnormal machine behavior—so that they can take action to avoid the impact and expense of equipment downtime.”
