AI and ML-Driven SAP Digital Core on Google Kubernetes Engine for Next-Generation Supply Chain Visibility
DOI:
https://doi.org/10.15662/IJARCST.2021.0403001Keywords:
SAP Digital Core, Supply Chain Visibility, Artificial Intelligence (AI), Machine Learning (ML), Google Kubernetes Engine (GKE), Predictive Analytics, Prescriptive Insights, Cloud-Native Infrastructure, Supply Chain Optimization, Real-Time Data ProcessingAbstract
The rapid evolution of global supply chains requires intelligent, scalable, and resilient systems capable of delivering real-time visibility across complex operations. This paper introduces an AI- and ML-driven SAP Digital Core deployed on Google Kubernetes Engine (GKE) to enable next-generation supply chain visibility. The proposed framework leverages SAP’s digital core integration capabilities, advanced machine learning models, and the scalability of GKE to process large-scale, multi-source supply chain data. AI-driven predictive analytics modules identify demand fluctuations, detect anomalies, and optimize resource allocation, while ML-based prescriptive insights recommend actionable strategies for procurement, logistics, and warehouse operations. GKE ensures elasticity, high availability, and fault-tolerant deployment of SAP applications, allowing enterprises to seamlessly scale with dynamic workloads. Experimental evaluations highlight significant improvements in supply chain transparency, forecasting accuracy, and decision-making efficiency. This research demonstrates how integrating AI, ML, and cloud-native architectures within the SAP Digital Core can empower enterprises with end-to-end visibility, adaptability, and resilience in next-generation supply chains.
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