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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
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License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 8

Published on: August 2026

AN FKF SPECTRAL FRAMEWORK FOR DIGITAL TWIN ENABLED PREDICTION

Shinde SM Harle SM

INDEPENDENT RESEARCHER

Article Status

Plagiarism Passed Peer Reviewed Open Access

Available Documents

Abstract

This study introduces an FKF-enabled intelligent supply-chain framework that integrates Artificial Intelligence (AI), Blockchain, Internet of Things (IoT), Digital Twins, and quantum optimization into a unified architecture. The FKF transform provides a mathematical spectral representation of supply-chain signals, enabling the identification of temporal shifts, modulation effects, multiscale patterns, demand fluctuations, and lead-time dynamics. These spectral features can be supplied to AI and machine-learning models to improve forecasting, anomaly detection, disruption prediction, and resilience assessment.

IoT devices continuously provide real-time operational data from transportation, inventory, production, and logistics processes, while Blockchain supports secure data sharing, traceability, and transaction transparency across supply-chain participants. Digital Twins complement these technologies by creating dynamic virtual representations of physical supply-chain systems, allowing alternative scenarios, disruptions, and recovery strategies to be simulated before implementation. Quantum annealing is incorporated to address selected computationally intensive combinatorial decisions, such as routing, scheduling, resource allocation, and logistics configuration.

By connecting FKF-based mathematical spectral intelligence with AI-driven analytics, trusted digital infrastructure, simulation capabilities, and emerging quantum optimization, the proposed framework provides an integrated pathway toward more predictive, adaptive, transparent, sustainable, and resilient supply-chain management. The content should be logically organized in a single paragraph, maintaining coherence and clarity throughout. Ensure that the abstract captures the research context, problem statement, approach, key results, and final conclusions in a balanced manner.

 

Keywords— Quantum Computing; Quantum Annealing; Logistics Optimization; Unit Load Device Configuration; Supply Chain Management; Artificial Intelligence; Digital Twins; Blockchain; Supply Chain Resilience; FKF Transform.

How to Cite this Paper

SM, S. & SM, H. (2026). An FKF Spectral Framework for Digital Twin Enabled Prediction. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(8), 1-9. https://doi.org/10.55041/ijcope.v2i8.208

SM, Shinde, and Harle SM. "An FKF Spectral Framework for Digital Twin Enabled Prediction." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 8, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijcope.v2i8.208.

SM, Shinde, and Harle SM. "An FKF Spectral Framework for Digital Twin Enabled Prediction." International Journal of Creative and Open Research in Engineering and Management 02, no. 8 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijcope.v2i8.208.

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  • Peer Review Type: Double-Blind Peer Review
  • Published on: Aug 25 2026
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