AI Articles and Analysis in Heavy industry

Explore articles and analysis related to artificial intelligence in heavy industry, including coverage of manufacturing, utilities, mining, and more.

PLUS
Emerj.com – 001 – AI at ExxonMobil-min

Artificial Intelligence at ExxonMobil – Two Applications at the Largest Western Oil Company

ExxonMobil is the largest investor-owned company in the world and the largest oil company by revenue in the Western world.

PLUS
Making AI Come 
to Life in Heavy 
Industry@2x-min

Making AI Come to Life in Heavy Industry – with Nikunj Mehta of Falkonry

While the steel industry may not be synonymous with AI adoption, steel manufacturers are not different from any other business in ensuring efficiency in their output and throughput. There are almost certainly opportunities for AI implementation across an industry worth hundreds of billions of dollars that currently lags behind in adopting AI technology.

Artificial Intelligence at Chevron 950×540

Artificial Intelligence at Chevron

Chevron is the second largest producer of oil in the United States (Exxon Mobil). The company is traded on the NYSE (symbol: CVX) and has a market capitalization of approximately $322 billion.  

Three Transformative AI Use-Cases in Manufacturing@2x

Three Transformative AI Use-Cases in Manufacturing – with Everton Paulino of SambaNova

This article has been sponsored by SambaNova Systems and was written, edited, and published in alignment with Emerj’s sponsored content guidelines.

AI at General Electric

Artificial Intelligence and Digital Twins at General Electric

General Electric (GE) was founded in 1889 by J.P. Morgan and Anthony J. Drexel who came together to finance Thomas Edison’s research and merge their companies together. Originally, GE was an industrial and consumer products company but today, more than 130 years later, GE has transformed itself into a multinational, digital industrial corporation ranked as the 33rd largest company in the United States by gross sales in 2020, according to Fortune 500.

Understanding Predictive Maintenance in Manufacturing

Understanding Predictive Maintenance in Manufacturing

The hypothesis is simple:

Equipment breakdowns or downtime is extremely expensive (imagine a train broken down on isolated tracks, hundreds of miles from the nearest depot)
Heavy equipment (engines, wind turbines, manufacturing machines) produce various streams of data (heat, vibration, time-series, etc)
Machine learning could be used to detect "failure patterns" in that data, helping businesses to maintain equipment health more effectively

How Machines and Robots Learn – the Progression of AI

How Robots Learn – an Interview with Jürgen Schmidhuber

This week, we speak with arguably one of the best-known folks in the domain of neural networks: Jurgen Schmidhuber. He's working on a lot of different applications now in heavy industry, self-driving cars, and other spaces.

Artificial Intelligence In Industrial Automation – Current Applications

Artificial Intelligence In Industrial Automation – Current Applications

Accenture forecast the Industrial Internet of Things could contribute $10 trillion to the global economy by 2030. The report also suggested that sensors, material tracking mechanisms, 3D printing, automated product design, robotics, and wearables could help manufacturers reduce costs and increase productivity. Predictive asset maintenance could potentially reduce equipment and machinery maintenance costs by up to 30% and result in up to 70% fewer breakdowns.

Heavy industry

Explore articles and analysis related to artificial intelligence in heavy industry, including coverage of manufacturing, utilities, mining, and more.