In an effort to revolutionise operational efficiency and combat costly equipment failures in Zimbabwe’s platinum sector, Midlands State University (MSU) mining engineering graduate Mufaro Handirimi has developed a groundbreaking predictive maintenance system targeting underground drill rigs, Mining Zimbabwe can report.
By Rudairo Mapuranga
This homegrown technological solution promises to significantly enhance the competitiveness of Zimbabwe’s mining operations through advanced data analytics and machine learning.
Handirimi, who serves as Head of Entrepreneurship at the Association of Junior Mining Professionals of Zimbabwe, has created a sophisticated application that shifts maintenance strategies from reactive to predictive for the Sandvik DD211 low-profile drill rig. The system specifically targets the drill and hydraulic modules of these machines, where most critical failures typically occur during underground operations.
The technical architecture employs a network of sensors, including accelerometers to monitor vibration patterns and flow rate sensors to track hydraulic system performance. These sensors utilise wireless connectivity to transmit real-time data from underground operations to a cloud-based analytics platform. At the heart of the system operates an Auto-Regressive Integrated Moving Average (ARIMA) time series module, which analyses equipment data patterns to calculate failure probabilities. A machine learning feedback loop enables the system to continuously refine its prediction accuracy, creating an increasingly intelligent maintenance solution.
Based on empirical evidence from comprehensive literature reviews, including McKinsey studies and a 2018 Barrick Gold case study, the system delivers a demonstrated 14% reduction in unplanned downtime. This improvement translates to substantial financial savings of approximately US$2,700 monthly per machine. For typical Zimbabwean platinum mines operating fleets of twenty or more drill rigs, this represents nearly US$40,000 in monthly savings through enhanced operational efficiency alone.
The innovation arrives at a crucial juncture for Zimbabwe’s mining industry, which accounts for 12% of the country’s GDP and dominates national export earnings. With Zimbabwe possessing the world’s second-largest platinum deposits, operational efficiency improvements directly impact the nation’s economic objectives. Handirimi’s system represents precisely the type of homegrown technological solution that can help achieve the government’s upper-middle-income economy vision.
This predictive maintenance application demonstrates how digital transformation can optimise traditional mining operations—particularly valuable given the industry’s challenges with persistent power shortages and foreign currency constraints. The project signals Zimbabwe’s growing capability to develop local solutions to industrial challenges, combining deep mining expertise with cutting-edge data analytics.
As the system progresses toward implementation, it stands to not only reduce operational downtime by 14% but also inspire a new generation of mining engineers to tackle industry challenges with innovative, locally developed technological solutions. Handirimi’s work embodies the potential for Zimbabwean professionals to lead the technological transformation of the nation’s most vital economic sector.
