Indian-Saudi Research Team Develops Blockchain System to Secure 3D Printing Sensor Data
2026-07-07 11:13
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en.Wedoany.com Reported - Researchers from Marwadi University and Parul University in India, in collaboration with King Khalid University in Saudi Arabia, have built and tested a blockchain-based system to secure sensor data during VAT photopolymerization 3D printing.

Research team develops blockchain-based IoT system to secure VAT photopolymerization sensor data

VAT photopolymerization cures photosensitive resin layer by layer using ultraviolet light, releasing volatile organic compounds (VOCs) that may degrade workplace air quality. The research team paired IoT sensors monitoring VOC concentration, resin temperature, and environmental conditions with a private Hyperledger Fabric network, using smart contracts to compare data against safety thresholds before submitting it to an immutable ledger. When readings exceed limits, the smart contract generates an alert and suspends data recording until the anomaly is resolved.

Research team develops blockchain-based IoT system to secure VAT photopolymerization sensor data

Research team develops blockchain-based IoT system to secure VAT photopolymerization sensor data

Researchers noted that previous blockchain applications in additive manufacturing mainly focused on supply chains, intellectual property, and digital twins, mostly remaining at the conceptual or simulation stage without experimental validation through real-time environmental monitoring. This system responds to that research gap. To evaluate blockchain's contribution to data integrity, the team conducted 20 simulated tampering attempts on both the Hyperledger Fabric system and a traditional MySQL database using identical hardware, including rolling back timestamps and modifying VOC values.

Beyond data integrity work, the study also examined the impact of printing parameters on emissions. Exposure duration showed the strongest correlation with VOC output, followed by light intensity, while layer thickness had minimal effect. The authors view the platform as a step toward compliance and predictive maintenance in VPP manufacturing, while noting that the system was tested on only one machine. The research was published in Scientific Reports.

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