Advanced Electronic Controller Circuits Enabling Production Processes and AI-driven KM in Industry 5.0

Abstract

The proposed paper presents a methodology for mapping electronic manufacturing control processes within a Knowledge Management (KM) framework, aligning with human-centric and transdisciplinary approaches. Specifically, the paper explores a Proportional-Integral-Derivative (PID) process for tuning production machinery, facilitating quality management and predictive maintenance through an AI-driven model. The PID circuit model is designed using the LTspice tool, while the entire production workflow is structured according to the Business Process Model and Notation (BPMN) standard. The model incorporates Artificial Intelligence (AI) to optimize machine control, establishing an advanced Digital Twin (DT) model that enables interactive human-system collaboration. The work further describes Knowledge Base (KB) data sources that support KM within Industry 5.0 environments, emphasizing AI-enhanced, user-centered control systems. Finally, the paper discusses new managerial roles and skill sets necessary for overseeing these integrated, human-centric KM systems in next-generation industrial applications.