Oracle and AI-Powered SAP Solutions for Reverse Logistics and Circular Supply Chains with Cloud-Based RTL-Level Threat Detection
DOI:
https://doi.org/10.15662/IJARCST.2024.0705003Keywords:
Oracle integration, Artificial Intelligence, SAP, Reverse logistics, Circular supply chains, Cloud computing, RTL-level threat detection, Predictive analytics, Blockchain security, Sustainability, Data protection, Machine learning, Digital transformation, Supply chain resilienceAbstract
The emergence of reverse logistics and circular supply chains has driven enterprises to adopt intelligent, secure, and sustainable digital ecosystems. This paper introduces a hybrid Oracle- and AI-powered SAP framework designed to enhance reverse logistics management, circular economy operations, and RTL (Register Transfer Level)–based threat detection through cloud-native integration. The proposed model leverages machine learning algorithms for dynamic asset tracking, return flow optimization, and waste reduction, while Oracle’s advanced analytics and SAP’s enterprise modules ensure seamless process coordination and compliance. A cloud-based AI security layer implements RTL-level threat detection to safeguard critical supply chain data and embedded systems from firmware-level attacks and unauthorized manipulations. Through blockchain-enabled transparency and predictive analytics, the system fosters real-time monitoring, secure data sharing, and sustainable decision-making. Case studies demonstrate improvements in material recovery efficiency, risk mitigation, and operational resilience. The study concludes that the integration of Oracle, AI, and SAP within a cloud-native architecture provides a transformative pathway toward secure, circular, and intelligent reverse logistics ecosystems.
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