AWS Utilizes Machine Learning for Predictive Maintenance
Amazon Lookout for Equipment from AWS is a machine learning service that simplifies predictive maintenance by leveraging real-time data streams with artificial intelligence.
Turning massive amounts of sensor data from critical equipment into actionable insights for maintenance and repair can be difficult, but Amazon Lookout for Equipment aims to simplify the process through a combination of machine learning and AWS data storage services.
AWS aims to turn sensor data into actionable insights. Image used courtesy of Gerd Altmann
AWS (Amazon Web Services) recently announced the availability of Amazon Lookout for Equipment, their new ML (machine learning) service for predictive maintenance of equipment. This development in equipment monitoring and maintenance combines the storage capabilities and artificial intelligence of AWS to help users get the most out of equipment monitoring sensor data.
Challenges of Predictive Maintenance
Predictive maintenance takes the data gathered from sensors placed on equipment and uses analysis and ML algorithms to predict when maintenance is needed. This provides a far more optimized approach to maintenance, resulting in minimal downtime, reduced maintenance and operation costs, longer equipment life, and improved productivity.
However, when a facility has numerous pieces of equipment and sensors collecting data on speed, temperature, and other key characteristics of performance, trying to aggregate, analyze, and use that data for predictive maintenance can be challenging. Amazon Lookout for Equipment endeavors to assist with processing that data and turning it into actionable information.
Amazon Lookout for Equipment
Using data such as temperature, pressure, vibration, rotations per minute (RPMs), flow rate, oxygen levels, and power, Amazon Lookout for Equipment can recognize anomalies and predict failures based on your equipment’s baseline data.
The AWS ML algorithms in Amazon Lookout process real-time data streams from equipment to recognize when sensor data has significantly departed from baseline performance. Because machine learning is involved, the predictive maintenance models are customized to each piece of equipment.
Amazon Lookout for Equipment can process up to 300 sensors for a single piece of equipment, ranging from a massive wind turbine to a critical electrical motor in a manufacturing production line.
Amazon Lookout can process sensors on equipment such as wind turbines. Image used courtesy of Matthias Böckel
Examples of anomalies that can be detected include changes in vibration data from rotating machinery (an early warning sign that a bearing is beginning to wear out) or increases in the winding temperature of electric motors that could point to problems with the integrity of the winding insulation.
Catching these problems before they lead to a shutdown allows maintenance and repair tasks to be planned ahead of time to minimize the impact on production and prevents more costly damage from occurring.
Benefits of Amazon Lookout for Equipment
In addition to the benefits of predictive maintenance, Amazon Lookout reduces problematic false flags, requires no expertise in ML, and provides alerts that grow more accurate over time.
Because Amazon Lookout works with real-time data streams and supports automated alerts and trouble tickets, users are able to respond faster to potential issues. These alerts can provide detailed information on what the alert is based upon, down to the individual sensors that have detected anomalous data.
Video used courtesy of AWS
Getting started is also very simple: users upload sensor data to Amazon S3 (Simple Storage Service) and provide the bucket location to Amazon Lookout. From there, Lookout for Equipment begins building models tailored to the equipment and the environment in which it works.
Amazon Lookout for Equipment is already in use by global leaders such as Siemens Energy, Cepsa, and Koch Ag and Energy Solutions, but its use is far from limited to energy applications. Any industry that depends on equipment and machinery can leverage Amazon Lookout’s data processing and machine learning algorithms to enhance its predictive maintenance programs in a straightforward, scalable way.
