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Supply Chain Management

Authors: null Brundha R; Meenaumadevi M Guide; null Mrs. K. Sugashini;

Supply Chain Management

Abstract

The Supply Chain Management (SCM) system is designed to enhance the efficiency, transparency, and resilience of supply chain operations. This project integrates advanced data analytics, machine learning, and real-time tracking to overcome the limitations of traditional SCM systems, such as demand volatility, inventory imbalances, and poor response to disruptions. By utilizing diverse data sources—including historical demand, market trends, and consumer insights. The system provides accurate demand forecasting and optimal inventory management. Key features include real-time visibility across the supply chain, predictive analytics for proactive decision-making, and a responsive structure that mitigates risks such as stockouts and overstocking. The system’s modular design supports scalability, enabling businesses to adapt quickly to market changes, streamline operations, and ultimately improve customer satisfaction and profitability.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
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