HEAT-SEER - A Real-Time Data Integration Experience Through Semantic Technologies in a Graphic Arts Company

Modern manufacturing companies leverage advanced technologies to monitor processes within their facilities. These technologies, rooted in Real-Time Operating Systems and Internet of Things paradigms, have already reached a certain level of maturity, and found widespread application across diverse sectors. Challenges arise, however, when factories operate outdated machinery and legacy systems or when processes lack proper automation. This is a common scenario in the graphic arts industry since the machinery used has a very long, useful life and it is expected to find printing machines that are over twenty years old. This work proposes a comprehensive management framework that utilises sensing systems and Artificial Intelligence technologies to acquire real-time information. Raw data is obtained from different aspects of the press through retrofitting techniques and incorporating specific sensors. At the same time, the most relevant information from the other systems existing in the factory has been considered. All the data stored on those systems are collected from their respective databases by “Heat-Seer”, an AI system guided by the historical information and business rules in a specific knowledge base. Currently, the solution is undergoing testing in a real-world environment, demonstrating promising results by enhancing efficiency and productivity.