AWS for Industries

Tag: AWS Machine Learning

Closing the manufacturing skills gap with generative AI

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% […]

Artificial intelligence in industrial welding produces near-real-time insights through virtually 100% sample sizes

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), […]

Selecting the best automatic machine learning to meet your manufacturing needs

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 […]

Tyson Foods Boosts Efficiency with Computer Vision and Machine Learning from AWS

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 […]

Predicting the failure of turbofan engines using SpeedWise Machine Learning.

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 […]

Oil Pump

Improving Safety and Logistics at Well Pads with Amazon Machine Learning Services

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 […]

How to Run What-if Scenarios for Trading Strategies with Amazon FinSpace

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 […]

Predicting all-cause patient readmission risk using AWS data lake and machine learning

It’s no secret that hospital readmissions impact patient outcomes and the financial health of healthcare providers globally. Specifically in the United States, the Agency for Healthcare Research and Quality (AHRQ) shows that readmissions are some of the costliest episodes to treat, with costs reaching in excess of $41.3B. Hospitals and healthcare providers are looking for […]