Category: Amazon Lookout for Equipment

This is a guest post co-written with Moulham Zahabi from Matarat. Probably everyone has checked their baggage when flying, and waited anxiously for their bags to appear at the carousel. Successful and timely delivery of your bags depends on a massive infrastructure called the baggage handling system (BHS). This infrastructure is one of the key […]

Predictive maintenance is a data-driven maintenance strategy for monitoring industrial assets in order to detect anomalies in equipment operations and health that could lead to equipment failures. Through proactive monitoring of an asset’s condition, maintenance personnel can be alerted before issues occur, thereby avoiding costly unplanned downtime, which in turn leads to an increase in […]

The last decade of the Industry 4.0 revolution has shown the value and importance of machine learning (ML) across verticals and environments, with more impact on manufacturing than possibly any other application. Organizations implementing a more automated, reliable, and cost-effective Operational Technology (OT) strategy have led the way, recognizing the benefits of ML in predicting […]

Predictive maintenance can be an effective way to prevent industrial machinery failures and expensive downtime by proactively monitoring the condition of your equipment, so you can be alerted to any anomalies before equipment failures occur. Installing sensors and the necessary infrastructure for data connectivity, storage, analytics, and alerting are the foundational elements for enabling predictive […]

Companies that operate and maintain a broad range of industrial machinery such as generators, compressors, and turbines are constantly working to improve operational efficiency and avoid unplanned downtime due to component failure. They invest heavily in physical sensors (tags), data connectivity, data storage, and data visualization to monitor the condition of their equipment and get […]

As the modern factory becomes more connected, manufacturers are increasingly using a range of inputs (such as process data, audio, and visual) to increase their operational efficiency. Companies use this information to monitor equipment performance and anticipate failures using predictive maintenance techniques powered by machine learning (ML) and artificial intelligence (AI). Although traditional sensors built […]

Machine downtime has a dramatic impact on your operational efficiency. Unexpected machine downtime is even worse. Detecting industrial equipment issues at an early stage and using that data to inform proper maintenance can give your company a significant increase in operational efficiency. Customers see value in detecting abnormal behavior in industrial equipment to improve maintenance […]