ifkad articles

A Methodology for Knowledge-based Modelling of Production Processes and Assessment of Application of AI-driven KM solutions

Alessandro Massaro, Demetrio Alessandro Trunfio, Giovanni Schiuma, Francesco Santarsiero

The goal of the proposed paper is to provide a methodology to map electronic processes of manufacturing control systems matching with Knowledge Management (KM) processes. Specifically, the paper discusses an example of Proportional-Integral-Derivative (PID) process tuning a production machine and enabling quality management and predictive maintenance processes. The PID circuital model is designed by the LTspice tool, and the whole production process is designed by the Business Process Model and Notation (BPMN) standard, including the role of the Artificial Intelligence (AI) in the optimization of the machine control. Furthermore, the work describes possible Knowledge Base (KB) data sources enabling KM in Industry 5.0 scenarios characterised by AI-data-driven PID-controlled systems. Finally, are discussed the new manager roles matching with the proposed KM system.

IN: Proceedings IFKAD 2024 – Translating Knowledge into Innovation Dynamics
PP: 2410-2417