A DATA DRIVEN CYBER PHYSICAL FRAMEWORK FOR REAL TIME PRODUCTION CONTROL INTEGRATING IOT AND LEAN PRINCIPLES

Abstract

The study titled A Data-Driven Cyber-Physical Framework for Real-Time Production Control Integrating IoT and Lean Principles investigated the convergence of data intelligence, adaptive automation, and process optimization to establish a responsive and self-regulating manufacturing environment. The primary objective of the research was to design and empirically validate a quantitative framework that integrates Internet of Things (IoT) connectivity, Cyber-Physical Systems (CPS) control logic, and Lean manufacturing methodologies to enhance operational efficiency, process reliability, and decision-making accuracy in real-time production systems. A total of 142 peer-reviewed research papers, industrial case studies, and empirical reports published between 2012 and 2021 were critically reviewed to synthesize the theoretical foundations and methodological insights that supported the development of the proposed model. The framework positioned IoT as the data backbone enabling real-time sensing, CPS as the adaptive control layer ensuring feedback precision, and Lean principles as the process foundation driving waste reduction and flow stability. Quantitative data were analyzed using regression, mediation, and moderation techniques to evaluate the causal pathways among IoT data quality, CPS responsiveness, and Lean performance outcomes. The results demonstrated that IoT data reliability and synchronization significantly improved CPS responsiveness, which in turn enhanced takt adherence, first-pass yield, and machine utilization, with CPS responsiveness acting as a full mediator between IoT integration and Lean efficiency. The study further established that Lean maturity moderated the relationship between CPS responsiveness and operational outcomes, indicating that process discipline amplified the benefits of digital transformation. Overall, the model achieved high explanatory power (adjusted R² = 0.68–0.81), confirming that data-driven integration yields measurable improvements in production performance, responsiveness, and stability. The findings substantiated that the fusion of IoT-enabled sensing, CPS-driven control, and Lean-based process management creates a cyber-physical ecosystem capable of self-optimization through real-time data feedback. This research contributed a holistic quantitative framework that bridges digital intelligence and operational excellence, offering both theoretical advancement and practical guidance for industries transitioning toward smart, adaptive, and waste-free manufacturing environments.