Tag: AWS Machine Learning

Manufacturing companies face significant challenges with unplanned equipment downtime, which leads to lost revenue and production delays. Maintenance teams often struggle to detect early warning signs of equipment failure due to resource constraints and a lack of advanced analytics expertise. To address these challenges, we are excited to announce the general availability of native anomaly […]

Manufacturers often tell us how workforce challenges affect their organizational productivity. If you feel this way, you are not alone. Every quarter, the U.S. National Association of Manufacturers, the trade association that consolidates manufacturer interests, polls CEOs on their primary business challenges. In the latest poll (2023 Fourth Quarter Manufacturers’ Outlook Survey), more than 71% […]

In metal-to-metal welding applications, automating inspections to detect weld defects early and often can help avoid costly product recalls, excessive scrap, rework, and other expenses associated with poor quality. Companies have found it challenging to implement such automation. IBM Smart Edge for Welding (SE4W) with AWS aggregates quality inspection capabilities based on artificial intelligence (AI), […]

Introduction Machine learning (ML) has become a core technology in manufacturing, but it can be difficult to know which ML services and tools are best for your industrial operations. We will define and explain the use cases of when to use different Amazon Web Services (AWS) ML services. In an age of rapid innovation, manufacturing […]

The National Football League (NFL) continues to evolve on and off the field. One of the biggest shifts in recent years is the league’s commitment to using data and technology to improve the sport. Amazon Web Services (AWS) supports this commitment as the NFL’s partnership with AWS continues to deepen. The Big Data Bowl exemplifies […]

The newest advanced metric tackles the hidden dynamics of punt and kickoff returns. The NFL Next Gen Stats team is here to give us the inside scoop. We have all witnessed a returner getting tackled a nanosecond after receiving a punt or kickoff. Holding onto the ball, let alone gaining a chunk of yardage, is a […]

Tyson Foods Inc. (Tyson Foods) processes millions of pounds of beef, pork, chicken, and prepared foods each week in its facilities worldwide and strives to achieve operational excellence throughout the production process. With large-scale operations, every manual step adds up, creating potential bottlenecks in the production process. That’s why the emerging technology team at Tyson […]

1. Introduction Equipment failure imposes an enormous burden on industry. It is estimated that unplanned downtime reduces plant productive capacity by between 5 and 20 percent and costs industrial manufacturers $50 billion annually. The cost to repair or replace equipment may be significant, but the true cost of unplanned equipment failure is its consequences. The […]

Introduction In remote upstream oil and gas facilities, such as well pads, energy companies frequently have various service contractors bringing in items, performing services, and removing items from the site. These facilities most often do not have permanent staff on location. It can be challenging for operators to know who is accessing the facilities. For […]

Introduction In an earlier blog post, we described an architecture for backtesting machine learning-based trading strategies on AWS. One of the key components in this architecture is the data management and analytics component. Depending on the specific use case, there are various options to implement this. Many companies adopt solutions based on data lakes and […]