ABSTRACT
The chemical manufacturing industries are at the forefront of innovation, exploring novel technologies through “smart manufacturing” and “industrial modernization” using computational approaches to cater to increasing market demands and stringent regulations. Digital design enables the manufacturers to understand and streamline the process development and production using process systems engineering tools. The present drive toward industrial automation advancements such as Industry 4.0, Pharma 4.0, and smart manufacturing also enables technological developments in research to percolate into industries to meet product quality, safety, and profitability challenges. It is envisaged that the promises of continuous manufacturing will be realized with the evolution of digitalization technologies in various stages of design, development, and implementation. Further, artificial intelligence (AI) and machine learning-based intelligent systems are gaining popularity in all engineering and science disciplines due to their ability to solve real-world challenges. In the chemicals field, digital transformation success necessitates a complete, holistic approach that considers the entire asset lifespan, from design to operations and maintenance. However, it has also led to far-reaching impacts on technology and the workforce worldwide. In the present work, 2 we concentrate on practical applications of AI in chemical manufacturing industries in the digital transformation of the chemical industry, discussing the challenges and technological impacts.
