AWS Public Sector Blog
Tag: predictive maintenance
The U.S. Air Force improves aircraft readiness with AI and predictive maintenance solutions
The US Air Force (USAF) is responsible for more than 5,400 aircraft with an average age of 28 years. Read this blog post to learn how USAF employs predictive maintenance solutions, powered by Amazon Web Services (AWS), to predict when aircraft need to be grounded for repairs or updates, which helps maintain mission readiness while lowering maintenance costs.
Optimizing operations for ground-based, extremely large telescopes with AWS
Ground-based, extremely large telescopes (ELTs), such as the Giant Magellan Telescope (GMT), will play a crucial role in modern astronomy by providing observations of the universe with remarkable clarity and detail. However, managing the vast amount of data generated by these instruments and supporting optimal performance can be a challenging task. AWS provides a suite of cloud-based solutions that can help address these challenges and streamline ELT operations. Learn how various AWS services can be used to optimize data storage, management, and processing, as well as advanced monitoring and remote continuity techniques, leading to improved overall performance and efficiency for ELTs.
How using AI for predictive maintenance can help you become mission ready
Predictive maintenance solutions involve using artificial intelligence (AI) algorithms and data analytics tools to monitor operations, detect anomalies, and predict possible defects or breakdowns in equipment before they happen. To help keep aircraft mission ready, the Air Force turned to PavCon, LLC, (PavCon), a woman-owned small business, to create an actionable predictive maintenance solution powered by Amazon Web Services (AWS).
Predictive Maintenance: Untapped Potential in Public Sector
Public sector organizations worldwide have responsibility for high-value assets and operations associated with utilities, public venues, roads, bridges, transit and mobility systems, airports, ports, and public health systems. Unexpected downtime can lead to critical outages that cost millions of dollars in lost productivity, but replacing or fixing broken equipment can also cost tens of thousands of dollars in extra expenses. Predictive maintenance analytics capture the state of the equipment, so you can identify potential breakdowns before they impact operations.