che_february-2025 - 4

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O
ne of the aspects of my job that I really enjoy is keeping in
touch with new and advanced technologies emerging from
the chemical process industries (CPI) - an interest that
traces back to my roots as an R&D engineer. Since products
from the CPI are used in just about every facet of our lives, the
technologies being developed and scaled up are as varied as the intended
applications, and many have far-reaching implications. Need,
economics and resource availability are some of the factors that influence
how quickly specific technical developments progress. And, automation
plays an increasingly important role in these advances - in
process and product development, scale up and manufacturing. Developments
in smart sensors and digitalization have already greatly influenced
many manufacturing sectors, including the CPI. Now, focus
is largely on artificial intelligence (AI), whereby vast data resources are
being harnessed to effect faster and more-advanced outcomes.
AI is a rather broad category of technologies that allow computers to
simulate human abilities related to learning, problem solving and creativity.
Machine learning (ML) and generative AI (Gen AI) fall under its umbrella.
In ML, computers make predictions based on data that they have
" learned. " The more-advanced Gen AI - made popular, for example,
by ChatGPT - enables a computer to generate new work that is similar,
but not the same as the data it has learned from. The increased use of AI
is one of the leading drivers in the growing demand for semiconductors,
and the chemicals that are used in their production.
Use of AI in the CPI is expanding. One of the better-known applications
in manufacturing is predictive maintenance. Additional applications
range from technical process and product developments to
business applications like supply-chain management [1]. One practical
example mentioned in this month's article " Make the Most of Alarms "
(pp. 34-36) is the incorporation of AI in alarm-management software to
help with operational safety and efficiency. Last month's issue describes
how AI is accelerating the development of advanced materials [2].
The capabilities of AI and its possible applications in the CPI are
many. It may help in designing more efficient catalysts and speed up
R&D. AI integrated with robotics, for example, is being explored as a
way to expedite discoveries in chemical synthesis [3]. New technological
advances are bound to be hastened as advanced automation
tools are implemented.
While AI undoubtedly holds great potentiaI, there are also concerns.
A study of 3,000 researchers and clinicians [4] revealed that over 90%
of those surveyed agreed that AI will help accelerate knowledge and
discovery, rapidly increase the volume of research conducted and
offer cost savings. Over 90%, however, were also concerned that AI
would be used for misinformation and about 85% were concerned
that AI would lead to weakened critical thinking.
AI is a powerful tool that offers exciting possibilities, but care is
needed in its adoption. As Kieran West, executive vice president,
Strategy, at Elsevier, said in a press release about
the study: " . . . high quality, verified information, responsible
development and transparency are paramount
to building trust in AI tools ... "
■
Dorothy Lozowski, Editorial Director
1. Bailey, M., Artificial Intelligence: Advancing Applications in the CPI,
Chem. Eng., June 2021, pp. 12-18.
2. Jenkins, S., Accelerating Materials Development with AI, Chem. Eng.,
January 2025, p. 18.
3. Ondrey, G., Autonomous synthesis robot uses AI to speed up chemical
discovery, Chem. Eng., March 2024, p. 8.
4. Elsevier, Insights 2024: Attitudes toward AI, July 2024, www.elsevier.
com/insights/attitudes-toward-ai.
4
CHEMICAL ENGINEERING WWW.CHEMENGONLINE.COM
FEBRUARY 2025
AI's potential in the CPI
http://www.accessintel.com http://www.elsevier.com/insights/attitudes-toward-ai http://www.elsevier.com/insights/attitudes-toward-ai http://WWW.CHEMENGONLINE.COM
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