STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Polymer & Composites Original Research Special issue

Blockchain Enabled IoT System for Tamper Proof Monitoring of Polymer Composite Manufacturing Quality

  1. Thote Priyanka Department of Computer Science and Engineering (Data Science), Vignan Institute of Technology and Science
  2. Sunil Kr Pandey Department of Information Technology, Institute of Technology & Science, Ghaziabad
  3. Rahul Koshti Department of Technology Management and Engineering, NMIMS, Hyderabad
  4. P. Vidyullatha Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur
  5. G. Simi Margarat Department of Information Technology, Agni College of Technology, Thalambur
  6. K. Ravikumar Department of Information Technology, Dhanalakshmi Srinivasan College of Engineering and Technology

Abstract

Ensuring real-time process compliance in resin-based polymer composite manufacturing remains a persistent challenge due to non-linear material behaviors, unpredictable curing dynamics, and fragmented sensor data pipelines. Traditional centralized monitoring architectures struggle to guarantee data integrity, auditability, and adaptive response under high-frequency environmental fluctuations. Most existing frameworks fall short in unifying trust, traceability, and time-critical decision-making particularly during critical cure-phase deviations due to limited integration of blockchain with intelligent sensor systems. To address this, we propose a blockchain-embedded smart monitoring architecture that fuses calibrated sensor streams with self-executing smart contracts for anomaly-aware compliance enforcement. Unlike rule-based dashboards or delayed post-process validation, our approach embeds real-time trigger logic directly within a decentralized ledger, ensuring tamper-evident control and instantaneous alerts. Experimental validation reveals a 34.6% reduction in alert latency and a 31.8% gain in anomaly detection accuracy compared to centralized benchmarks. The system also sustained a 0% rollback rate across three full resin curing cycles, with blockchain commit latency stably confined under 2.3 seconds (99th percentile), as evidenced by histogram analysis. This work introduces a new paradigm for intelligent, secure, and transparent process supervision in advanced manufacturing. By coupling decentralized trust mechanisms with embedded smart sensing, it paves the way for auditable-by-design frameworks suited for Industry 5.0 and critical safety-bound composite workflows.

Keywords

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