AI-Driven Orchestration for Turnaround Time and SLA Optimization across E-Commerce and Cell Therapy (Healthcare) Logistics

Author(s)	Ashish Patil
Country	India
Abstract	In the evolving landscape of global supply chains, the need for fulfillment systems that are both highly scalable and deeply precise has never been greater. E-commerce networks demand rapid, high-volume coordination across multiple nodes, while personalized healthcare therapies, such as cell and gene therapies, require individualized, traceable, and time-sensitive execution. This paper presents a unified architecture for predictive AI-driven decision systems that optimize fulfillment, capacity planning, and turnaround time in both environments. By combining real-time data ingestion, machine learning–based risk detection, and optimization logic enhanced by human-in-the-loop controls, the proposed system demonstrates measurable gains in operational agility, SLA compliance, and patient service levels. The framework is validated through use cases drawn from enterprise-scale e-commerce fulfillment and FDA-regulated cell therapy logistics, showing broad applicability across sectors [1]–[3].
Field	Engineering
Published In	Volume 6, Issue 4, July-August 2024
Published On	2024-08-09
DOI	https://doi.org/10.36948/ijfmr.2024.v06i04.48544
Short DOI	https://doi.org/g9qxnh

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International Journal For Multidisciplinary Research