Secure AR-enabled Smart Manufacturing Framework Integrating Machine Learning and Blockchain

Abstract

Augmented reality (AR) is increasingly adopted in Industry~4.0 to enhance operational efficiency and workplace safety. Yet, most implementations examine productivity and safety in isolation and seldom integrate AR with complementary technologies. This study proposes a secure AR-enabled framework for smart manufacturing that incorporates machine learning for predictive optimization and blockchain for tamper-proof data integrity. The framework is formalized through an algorithmic workflow, a six-layer system architecture, and mathematical models quantifying productivity, safety, economic viability, and user engagement. A simulation-based evaluation with 50 participants across five representative manufacturing tasks indicated measurable improvements: 25% faster task completion, 15% error reduction, 30% downtime reduction, 40% safety improvement, and 35% shorter training duration. While these results provide quantitative evidence of AR’s dual role in enhancing efficiency and safety, the findings are limited to controlled simulations and do not fully capture the variability of industrial environments. Future validation in live manufacturing contexts is therefore necessary to establish practical applicability.