Practical Use Cases for Artificial Intelligence and Machine Learning | AIChE

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Practical Use Cases for Artificial Intelligence and Machine Learning

Plant Operations

Artificial intelligence (AI) and machine learning (ML) tools are being applied in the process industries to improve a variety of operations and maintenance tasks.

Artificial intelligence (AI) and machine learning (ML) are ready to be deployed on the plant floor. In the past, technical and economic hurdles made application impractical, but those hurdles have been overcome and the chemical process industries (CPI) are now embracing AI and ML technology in their plants for a variety of operations and maintenance use cases. Before getting into more detail about potential applications, let’s cover some basics on AI and ML.

It’s likely that you are familiar with the general idea of AI, which is defined as “the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings” (1). Fields as diverse as theology, mathematics, philosophy, and writing have speculated about the concept of AI for centuries, even though the term to describe it would not come about until much later (2). The term was officially coined in 1956 as part of the “Dartmouth Summer Research Project on Artificial Intelligence” (3) and is attributed to Dartmouth College’s John McCarthy, considered to be one of the founders of AI, and three other researchers involved in the project.

ML is a branch of AI that pertains to the ability of a software application or machine/system to learn through experience, becoming more intelligent over time through data and algorithms rather than programming. The term ML has been in existence almost as long as the term AI; it was introduced as part of a 1959 article by IBM’s Arthur L. Samuel entitled “Some Studies in Machine Learning Using the Game of Checkers” (4)...

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