Improving the efficiency of the plastic waste processing process using industry 4.0 solutions

Abstract

The article focuses on the role of artificial intelligence (AI) in Industry 4.0, with particular emphasis on its application in the plastic waste processing process. In the face of growing challenges related to waste management and environmental protection, digital technologies play a key role in optimizing recycling processes, increasing efficiency and minimizing raw material losses. The article discusses in detail the use of AI in waste sorting automation, where intelligent algorithms using vision systems and spectral sensors allow for precise identification and segregation of different types of plastic. Solutions based on digital twins are also presented, which allow for simulation and optimization of production processes in a virtual environment. The author cites examples of AI implementations in recycling plants, such as AMP Robotics, Recycleye and ZenRobotics, which increased the efficiency of segregation and recovery of secondary raw materials by up to 30-40%. At the same time, the article analyzes the challenges related to the implementation of AI in the industrial sector. Key threats include the risk of cyberattacks, the growing dependence on autonomous systems, and potential social consequences, such as job losses in traditional industrial sectors. The author emphasizes the need to implement appropriate legal regulations, security policies, and educational programs that will allow for the sustainable use of artificial intelligence. In summary, the article presents AI as a key element of the transformation of industry 4.0, which can contribute to significant improvements in plastic waste processing. However, full use of the potential of this technology requires a strategic approach that takes into account both technological, social, and environmental aspects.