Jere Siivonen

Papers

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About

Jere Siivonen is a researcher focused on bridging the gap between advanced digital manufacturing and the practical realities of small and medium enterprises (SMEs). His work centers on industrial data pipelines, Industry 4.0 adoption, and the visualization of complex manufacturing data models. Siivonen’s key contribution is developing methods to help SMEs integrate physical legacy machinery with Industrial Internet of Things (IIoT) systems, enabling data-driven processes without requiring complete overhauls. His most cited paper, "Industrial Data Pipelines for Manufacturing Applications" (2023, 6 citations), directly addresses the struggle SMEs face in utilizing industrial data. He also advanced the D-BEST methodology for deploying services in robotics and production automation pilot lines (2024, 3 citations), aiming to increase utilization of research environments for test-before-invest and lifelong learning. Additionally, his case study on visualizing manufacturing system data models (2024, 2 citations) tackles the abstraction barrier that prevents SMEs from adopting Industry 4.0 practices. Through these efforts, Siivonen is making industrial digitalization more accessible and actionable for smaller manufacturers.