REAL-TIME MANUFACTURING ANALYTICS THROUGH INDUSTRIAL IoT, ERP, AND DIGITAL TWIN INTEGRATION

Abstract

The rapid evolution of Industry 4.0 technologies has accelerated the adoption of Industrial Internet of Things (IIoT), Enterprise Resource Planning (ERP), Digital Twin technology, cloud computing, and artificial intelligence in modern manufacturing environments. Traditional manufacturing systems primarily depend on periodic production reports and manually updated enterprise databases, limiting the ability of organizations to perform real-time operational analysis and intelligent decision-making. Industrial IoT devices continuously generate operational data from machines, production lines, inventory systems, and environmental sensors, while Digital Twins provide virtual representations of physical manufacturing assets for continuous monitoring and simulation. This paper proposes a Real-Time Manufacturing Analytics architecture integrating Industrial IoT, Enterprise Resource Planning, and Digital Twin technologies into a unified intelligent manufacturing platform. The proposed framework supports continuous operational monitoring, predictive analytics, production optimization, equipment health assessment, and enterprise-wide decision support. Experimental analysis demonstrates improvements in production efficiency, predictive maintenance, inventory management, operational visibility, and manufacturing productivity while providing a scalable foundation for Industry 4.0 smart manufacturing environments. Keywords: Industrial Internet of Things, Enterprise Resource Planning, Digital Twin, Smart Manufacturing, Manufacturing Analytics, Industry 4.0, Predictive Maintenance, Real-Time Decision Support.