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

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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Publication Details

Journal
Journal of Computers Mechanical and Management
Published
2025-08-31
DOI
https://doi.org/10.57159/jcmm.4.4.25208
Primary Topic
Digital Transformation in Industry
Type
article
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article

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

Anamika Singh, Abhishek Singh, Manisha Pipariya
Journal of Computers Mechanical and Management
Digital Transformation in Industry
article

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

Anamika Singh, Abhishek Singh, Manisha Pipariya
article en

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.

Journal of Computers Mechanical and ManagementVol. 4(4)
Birla Institute of Technology, Mesra (IN), Spicer Adventist University (IN), MIT Art, Design and Technology University (IN)
Openalex Percentile: Top 64%
Digital Transformation in Industry
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Secure AR-enabled Smart Manufacturing Framework Integrating Machine Learning and Blockchain — Anamika Singh, Abhishek Singh, et al. · Journal of Computers Mechanical and Management (2025) | TGRS Research Map | TGRS