Academic Journal

Optimal Inventory Planning for Iron Ore Processing: A Mathematical Perspective from Ansteel Mining Corporation

Bibliographic Details
Title: Optimal Inventory Planning for Iron Ore Processing: A Mathematical Perspective from Ansteel Mining Corporation
Authors: Azul, Alba
Publisher Information: Zenodo, 2023.
Publication Year: 2023
Subject Terms: 9. Industry and infrastructure, 8. Economic growth, Optimal Inventory Planning, Iron Ore Processing, Data-Driven Decision-Making, Mathematical Models, Production Scheduling, Resource Allocation, Mining Industry, Ansteel Mining Corporation, 12. Responsible consumption
Description: Efficient inventory planning is critical for optimizing iron ore processing operations in the mining industry. Ansteel Mining Corporation recognizes the significance of data-driven decision-making in achieving optimal inventory management. This study presents a mathematical perspective on inventory planning for iron ore processing at Ansteel Mining Corporation. The research highlights the development and application of mathematical models to optimize inventory levels, production scheduling, and resource allocation. By leveraging historical process data and real-time sensor information, the mathematical models aim to minimize inventory costs, reduce production bottlenecks, and ensure timely order fulfillment. The case study showcases the successful implementation of data-driven inventory planning strategies, leading to improved operational efficiency, reduced waste, and enhanced profitability. The insights gained from this study provide a valuable framework for the mining industry to adopt mathematical techniques in inventory planning for sustainable and economically viable mining operations.
Document Type: Article
Language: English
DOI: 10.5281/zenodo.8175441
DOI: 10.5281/zenodo.8175440
Rights: CC BY
Accession Number: edsair.doi.dedup.....20d10c80d40bcb0cfc9bcd854d753c0a
Database: OpenAIRE
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