| Author(s) | Collection number | Pages | Download abstract | Download full text |
|---|---|---|---|---|
| Zatserkovna R. S., Зацерковний Р. Г., Степанець В. О. | № 1 (68) | 54-60 |
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In recent years, the packaging industry has been characterized by dynamic technological development and the rapid introduction of the latest technologies. Artificial intelligence algorithms and machine learning tools have found a number of new applications in this industry; and the integration of artificial intelligence and machine learning technologies into the packaging industry has ushered in a new era of opportunity and innovation in the industry. Using advanced algorithms and data analytics, AI and machine learning tools help packaging companies optimize their operations, improve product quality, and meet consumer demands. These technologies enable the introduction of entirely new technologies: predictive maintenance of printing presses; real-time packaging monitoring; and adaptive manufacturing, which helps to increase productivity and save money. The insights provided by AI technologies facilitate the development of any packaging solution, helping to improve the efficiency of the entire production process. This article highlights the potential of AI and machine learning in the packaging industry using specific examples.
The purpose of the article is to review the key AI and machine learning technologies used in the packaging industry in order to provide a comprehensive understanding of the latest trends in this field.
The article describes quality control and defect detection in the process of packaging production. The necessity of predictive maintenance of production equipment is substantiated and an example of the organization of this type of maintenance in a packaging company is provided. Finally, an example of the use of artificial intelligence to improve the environmental friendliness of packaging production, waste analysis and tracking of packaging products is presented.
Keywords: packaging, information technology, artificial intelligence, machine learning.
doi: 10.32403/1998-6912-2024-1-68-54-60
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