Enhancing Hauling Efficiency in Mining: A Data-Driven Approach to Productivity Optimization - Archive ouverte HAL
Poster De Conférence Année : 2024

Enhancing Hauling Efficiency in Mining: A Data-Driven Approach to Productivity Optimization

Anita Dehoux
  • Fonction : Collaborateur

Résumé

This study explores the optimization of hauling efficiency in mining operations through a data-driven approach. By analyzing real-time performance metrics from a Nickel mine in New Caledonia over three years, the research quantifies the impact of key factors such as cycle time and payload on productivity and production. The findings reveal a weak correlation between productivity and total production, indicating that maximizing productivity alone does not ensure higher production. Instead, the study highlights the importance of optimizing cycle time and operational factors such as fleet availability and shift management for improving overall efficiency and profitability. The research underscores the need for a broader focus beyond productivity metrics to enhance production in mining operations.
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Dates et versions

hal-04681368 , version 1 (29-08-2024)

Identifiants

  • HAL Id : hal-04681368 , version 1

Citer

Nicolas Guerin, Anita Dehoux. Enhancing Hauling Efficiency in Mining: A Data-Driven Approach to Productivity Optimization. Indaba Deep Learning 2024, Sep 2024, Dakar (Sénégal), Senegal. ⟨hal-04681368⟩
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