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		<www.jsetms.com>
		<Title>SUPPLY CHAIN DELAY PATTERN ANALYSIS</Title>
		<Author>1 Vijayata Ramteke, 2 B Akhil Paul, 3 P Bhuvanesh, 4 Saniya Firdous</Author>
		<Volume>03</Volume>
		<Issue>09</Issue>
		<Abstract>The Supply Chain Delay Pattern Analysis system is a data analytics and visualization platform designed to identify analyze and monitor delays that occur across different stages of the supply chain Modern supply chains involve suppliers manufacturers warehouses transportation providers and customers making timely delivery an important factor in operational efficiency Delays in any stage can affect inventory levels production schedules customer satisfaction and overall business performance The proposed system collects appropriate supplychain information such as order dates supplier details shipment dates expected delivery dates actual delivery dates transportation modes warehouse locations product categories and delivery status The system processes this information to calculate important Key Performance Indicators KPIs such as total shipments delayed shipments average delay duration ontime delivery rate supplier performance and transportation delay rate The dashboard presents analyzed information through interactive charts graphs tables maps and KPI cards Supplychain managers can compare delays across suppliers transportation modes warehouses product categories and geographic regions Timebased filters allow users to analyze daily weekly monthly quarterly or yearly delay patterns The system can identify recurring delay patterns and highlight areas where delivery performance is below expectations Trend analysis can help managers understand whether delays are increasing or decreasing over time The system can also identify relationships between delays and factors such as transportation mode supplier warehouse route or product category while avoiding unsupported assumptions about the cause of a specific delay Overall the Supply Chain Delay Pattern Analysis system provides a centralized platform for transforming supplychain data into meaningful operational insights It reduces manual reporting efforts and supports better logistics planning supplier evaluation inventory management and delivery optimization Future enhancements can include AIbased delay prediction routerisk analysis demand forecasting realtime shipment tracking automated alerts and predictive supplychain planning</Abstract>
		<permissions>
<copyright-statement>Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved</copyright-statement>
<copyright-year>2026</copyright-year>
</permissions>
		</www.jsetms.com>
		