Enhancing Short-Interval Controls in Open-Pit Mining through the Integration of Business Intelligence Analytics and the Internet of Things: A Case Study of Lumwana Mining Company

Abstract

The integration of Business Intelligence (BI) analytics with Internet of Things (IoT) technologies offers significant potential to optimize operational efficiency in open-pit mining operations. This paper investigates the application of these technologies to enhance Short-Interval Controls (SIC) at Lumwana Mining Company, one of Africa's largest open-pit mining sites. The research focuses on leveraging IoT-driven sensor networks, machine telematics, automated data acquisition systems, and BI analytics to derive actionable insights. By employing advanced AI-driven analytics, including predictive modeling and data visualization, the study aims to optimize production scheduling, improve equipment productivity, and reduce idle time. A mixed-methods approach is adopted, combining quantitative analysis of real-time operational data with qualitative insights from industry experts to evaluate the effectiveness of BI-IoT integration for SIC. The findings will contribute new knowledge to the field of data-driven mining operations, offering a flexible and scalable model for improving efficiency, sustainability, and cost management in open-pit mining. Practical recommendations derived from this study will assist mining engineers, data analysts, and decision-makers in effectively implementing digital transformation strategies to optimize mining processes.