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

Authors

  • Anamika Singh Sai Balaji Education Society, SPPU Program, Pune, Maharashtra, India 411057
  • Manisha Pipariya MITCOM, MIT Art, Design and Technology University, Pune, Maharashtra, India 412201
  • Abhishek Singh Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India 835215

DOI:

https://doi.org/10.57159/jcmm.4.4.25208

Keywords:

Augmented Reality, Industry 4.0, Smart Manufacturing, Machine Learning, Blockchain, Safety Management

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.

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Published

31-08-2025

How to Cite

Singh, A., Manisha Pipariya, & Singh, A. (2025). Secure AR-enabled Smart Manufacturing Framework Integrating Machine Learning and Blockchain. Journal of Computers, Mechanical and Management, 4(4), 29–34. https://doi.org/10.57159/jcmm.4.4.25208