The Prospect of Artificial Intelligence in Chemical Process Industries
Abidemi Awojuyigbe Mentor: Emmanuel A. Dada Department of Chemical Engineering Introduction: Artificial intelligence is a subpart of computer science that focuses on the development of programs to enable computers to perform tasks that usually require human intelligence. In this project, we shall explain AI in general, analyze the logic behind AI, and identify promising current and future opportunities of AI Application in chemical industries, where AI can be implemented to enhance operations in chemical industries. In this project, we shall focus on the implementation of artificial intelligence on a distillation column. Materials and Methods: For this study, we carried out extensive literature review on applications of AI in the chemical industries. We researched machine-learning applications to increase efficiency of catalyst formation processes. This research focused on the significant impact and values of Artificial Intelligence in chemical industries over natural human intelligence. Deep learning was applied to solve high-level functions like modeling, simulation, and optimization of chemical processes. Results and Discussion: Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. There are two kinds of AI: Artificial Narrow Intelligence (ANI), for example in smart speaker, self-driving cars, and Artificial General Intelligence that can do anything humans can do. Machine Learning: It is the concept that gives a computer program ability to learn andadapt to new data without human intervention or without being explicitly. Machine learning is a field of artificial intelligence (AI) that keeps a computer's builtin algorithms current regardless of changes in the worldwide economy. Artificial Intelligence is beginning to make its way into the chemical industry; it is now being used to reduce carbon footprint by chemical companies. The chemical industry is now beginning to adopt artificial intelligence in order to improve operational efficiency, reduce costs and help cut down on greenhouse gas emissions. Application of AI in chemical process modeling: An AI-based approach to chemical modeling encompasses processes such as catalyst deactivation in reactors. The most common methods of artificial intelligence in chemical modeling are ANN and fuzzy logic. Application of AI in optimization in chemical processes: Chemical process optimization generally refers to finding the best solution from various alternatives of operating variables in order to maximize or minimize a desired objective. Application of AI in fault detection: The utilization of neural networks to identify faults is becoming increasingly sought after in the chemical industry. Neural networks have a high potential for capturing non-linear relationships. Conclusions: We are currently researching ways to apply artificial intelligence, specifically on a distillation column in the chemical industry. We are working to use artificial intelligence to increase the efficiency of chemical processes in the chemical industry. This research would examine possible applications of artificial intelligence on a distillation column. We aim to analyze the logic behind artificial intelligence and identify possible applications in the chemical industries. References: 1. Dimitrov, Tanja; Kreisbeck, Christoph; Becker, Jill S.; Aspuru-Guzik, Alan; Saikin, Semion K.,“Autonomous Molecular Design: Then and Now”, ACS Applied Materials & Interfaces (2019),11(28), 24825-24836 2. Haijar, Zeinab; Tayyebi, Shokokfe; Ahamadi, Mohammad H., “ Application of AI in Chemical Engineering”, Chapter 20 , 2018 Awardee and Atudent: Dr. Emmanuel Dada is an Assistant Professor in the Chemical Engineering Department with research interests in artificial intelligence and clean energy. Abidemi Awojuyigbe is a senior, majoring in Chemical Engineering Page 150 of 3
