By Sitetrail Research Team

Artificial intelligence (AI) is transforming the world in ways that we could not have imagined a few decades ago. From self-driving cars to smart assistants, AI is making our lives easier, safer, and more productive. But AI is not only limited to these common and familiar applications. Many other amazing and surprising uses of AI are changing various fields and industries. In this article, we will explore some of these applications and how they are impacting the world. 

AI in Chemical Engineering 

Chemical engineering is the branch of engineering that deals with the design, operation, and optimization of chemical processes and systems. Chemical engineers use mathematical models, simulations, and experiments to understand and control the behavior of chemical reactions, separations, and transport phenomena. AI can help chemical engineers to solve complex problems, improve efficiency, and discover new possibilities. 

One of the areas where AI can assist chemical engineers is process systems engineering (PSE), which is the discipline that focuses on the integration of different components and processes in a chemical plant. PSE involves tasks such as process design, synthesis, analysis, control, scheduling, and optimization. AI can help PSE by providing intelligent tools and methods for data analysis, modeling, optimization, and decision-making. 

While major efforts to develop AI methods for chemical engineering problems started in the early 1980s, it is remarkable that some researchers (for instance, Gary Powers, Dale Rudd, and Jeff Siirola) were investigating AI in PSE in the late 1960s and early 1970s. Written by Venkat Venkatasubramanian, a professor of chemical engineering at Columbia University, in his book “AI in Process Systems Engineering”. 

Some of the AI techniques that are used in PSE include artificial neural networks, fuzzy logic, genetic algorithms, expert systems, and machine learning. These techniques can help PSE in various ways, such as: 

• Artificial neural networks can be used to model nonlinear and complex phenomena, such as reaction kinetics, thermodynamics, and fluid dynamics. They can also be used to estimate unknown parameters, predict process behavior, and identify faults and anomalies. 
• Fuzzy logic can be used to handle uncertainty and imprecision in data and models, such as measurement errors, sensor noise, and linguistic variables. Fuzzy logic can also be used to design robust and adaptive controllers, such as fuzzy PID controllers, that can cope with disturbances and changes in the process. 
• Genetic algorithms can be used to optimize process design and operation, such as finding the optimal values of design variables, operating conditions, and control parameters. Genetic algorithms can also be used to perform multi-objective optimization, such as minimizing cost and maximizing performance. 
• Expert systems can be used to capture and apply human knowledge and experience in solving PSE problems, such as diagnosis, troubleshooting, and decision support. Expert systems can also be used to …read more

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