Design of an AI-driven Architecture with Cobots for Digital Transformation to Enhance Quality Control in the Food Industry

In recent years, the rapid evolution of smart technologies has spurred enterprises to undergo digital transformations, revolutionizing their business processes and operations. This shift, known as Digital Transformation, has permeated diverse sectors, particularly impacting production systems. Notably, Artificial Intelligence (AI) and robotic automation have emerged as pivotal drivers in this transformation, promising enhanced efficiency and innovation in industrial digitization. This paper presents a novel architecture designed to facilitate digital transformation within enterprises, harnessing the capabilities of advanced collaborative robots (cobots) and cutting-edge image segmentation techniques. Focused on a practical scenario within a food production environment, our proposed architecture aims to seamlessly integrate a cobot and a camera in an automatic system for efficient cardboard disposal. Specifically, our attention is drawn to the challenge of differentiating sections of food packaging suitable for disposal from those contaminated with stains or organic residues, a task with significant implications for waste management efficiency. By leveraging a cloud-based architecture and deploying AI algorithms for image segmentation, localization, and robot guidance, our study showcases the tangible benefits and practical applicability of these methodologies in real-world settings. This research not only highlights the potential of AI-driven solutions in addressing specific industrial challenges but also underscores the broader impact of digital transformation on optimizing operational processes and driving innovation across sectors.