AI Articles and Reports in Heavy industry
Explore articles and reports related to artificial intelligence in heavy industry, including coverage of manufacturing, utilities, mining, and more.
McKinsey reported that most oil and gas operators have not maximized the production potential of their assets. A typical offshore platform, according to the 2017 report, runs at about 77% of its maximum production potential. Industry-wide, the shortfall comes to about 10 million barrels per day, or $200 billion in annual revenue.
With the entrance of artificial intelligence and its capabilities of recognizing temperature, vibration, and other factors from sensors pre-built into machinery and vehicles, business leaders in heavy industry might be interested in the possible opportunities of predictive and preventative maintenance applications.
Businesses today around the world have some portion of their operations being automated, which concurrently has meant that a lot of data about these processes is being collected (from sensors or internal company data etc). A combination of AI, big data analytics, and data science techniques seem to be a growing trend in many industry sectors, with predictive analytics being one of the most well-known.
Over the past decade, the industrial sector has seen major advancements in automation and robotics applications. Automation in both continuous process and discrete manufacturing, as well as the use of robots for repetitive tasks are both relatively standard in most large manufacturing operations (this is especially true in industries like automotive and electronics).
Relative to banking, finance or healthcare, construction is still a small market for artificial intelligence and emerging applications are focused on finding patterns in large datasets which would either be too difficult for humans to process or would take them too long. Over the course of this article, we aim to answer the following questions: