DIGITAL THREAD ARCHITECTURE FOR TRACEABLE AND INTELLIGENT ADDITIVE MANUFACTURING SYSTEMS

Abstract

Additive manufacturing has become a critical technology for Industry 4.0 by enabling flexible production, customized component fabrication, and reduced material consumption. However, maintaining complete traceability, interoperability, and intelligent decision-making across the manufacturing lifecycle remains a significant challenge. This paper proposes a Digital Thread architecture for traceable and intelligent additive manufacturing systems by integrating Industrial Internet of Things (IIoT), Digital Twin technology, machine learning, cloud computing, manufacturing execution systems, blockchain-based traceability, and intelligent analytics. The proposed methodology establishes a continuous data flow across design, simulation, production, inspection, maintenance, and lifecycle management stages. The framework enables real-time monitoring, quality tracking, predictive analysis, process optimization, and secure information exchange throughout the manufacturing lifecycle. Experimental evaluation demonstrates improvements in traceability, data interoperability, quality assurance, operational visibility, production efficiency, and decision-making accuracy. The proposed architecture provides a scalable and intelligent solution for next-generation additive manufacturing environments supporting sustainable Industry 4.0 transformation. Keywords— Digital Thread, Additive Manufacturing, Traceability, Digital Twin, IIoT, Intelligent Manufacturing, Machine Learning, Industry 4.0.