Peko Ivan

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About

Peko Ivan is a forward-thinking researcher at the intersection of artificial intelligence, digital twin technology, and advanced manufacturing systems. His work focuses on revolutionizing production environments through the integration of AI-driven forecasting and simulation, particularly within learning factory settings. Ivan’s most-cited paper, "Artificial Intelligence Forecasting of Digital Twin Assembly Line Performances Within Learning Factory Environment" (2024), introduces a novel framework that leverages AI to predict and optimize assembly line performance in real time, bridging the gap between virtual models and physical operations. This contribution is pivotal for Industry 4.0, enabling smarter, more adaptive manufacturing processes. Although early in his citation impact, with 1 citation to date, Ivan’s research is gaining traction among scholars and practitioners exploring digital twins and smart factories. His work is notable for its practical application in educational learning factories, where it serves as a tool for training and innovation. Ivan’s dedication to merging AI with industrial engineering positions him as an emerging voice in the future of automated and intelligent production systems.