Optimization of Chemical Manufacturing with Artificial Intelligence

1. Ms Pranali G Puri, COET, Akola

2.Ms Samruddhi Gawai, COET, Akola

(Students Chemical Engineering)

Abstract:

.The chemical industry once dominated by manual processes and rigid systems, is now experiencing a technological revolution. Artificial intelligence (AI) is no longer a futuristic concept but a real time. The chemical manufacturing industry faces significant challenges in optimizing Production process, reduction waste, and minimizing environmental impact. Artificial Intelligence (AI) offers a promising solution to these challenges. This study explores the application of Al techniques including machine learning and optimization algorithms to optimize chemical Manufacturing processes.

•AI has immense potential in the chemical manufacturing industry, improving processes and speeding up the development of optimized solutions like automate tasks, detect downtime and leakages, optimize resource and energy consumption, and enhance quality control in chemical manufacturing.

• Predictive analytics is a powerful tool that allows manufacturing establishments to prevent issues from occurring and evaluate business decisions.

• AI can solve the most common issues encountered by chemical manufacturers, including: downtimes on the production line, leakages and contamination, unstable and compromised quality, low or fluctuating yields, excessive waste production, inefficient resources use, lengthy discovery process or energy use optimization

• Chemical manufacturers can utilize deep learning models to conduct research at the molecular level, enabling them to identify highly efficient solutions and enhance their current formulas.

Results show that the AI-optimized process achieves:-

12% reduction to energy consumption

15% reduction in waste generation.

8% increase in productivity.

 This research highlights the potential of Al in transforming the chemical manufacturing Industryand contributing to a more Sustainable future. The findings of this study can be applied to various chemical manufacturing processes, enabling industries to reduce their environmental Footprint while improving efficiency and productivity.

Keywords:artificial intelligence, optimization, deep learning, machine learning, AI algorithms.

DOI link – https://doi.org/10.69758/GIMRJ/2505I5VXIIIP0028