Anonymous Mining Company

Maintaining predictable equipment readiness across multiple operating sites is a persistent challenge in metals and mining, where unplanned downtime directly constrains throughput and revenue. This mining operation needed to determine how many units of heavy equipment were available at any given moment under realistic maintenance conditions — and whether existing inspection regimes were calibrated correctly or simply inherited from outdated practice. Without a quantitative model, planners had no reliable method to test how changes in maintenance frequency, equipment quantities, or site configurations would affect fleet availability. The result was a mix of over-inspection at some sites and unquantified availability risk at others.

To address the availability uncertainty, the organization partnered with Rockwell Automation to build a discrete-event simulation using Arena Simulation software — a digital twin approach that modeled the full maintenance lifecycle of the equipment fleet. Every maintenance activity was catalogued along with its duration and frequency, creating a virtual replica of fleet operations. The model was then used to run scenarios varying the number of operational sites, equipment quantities, and maintenance interval reductions to identify which configurations met target availability thresholds. This allowed planners to stress-test assumptions in the model before committing to operational changes, replacing guesswork with evidence-based scheduling across all sites.

The simulation identified the minimum viable equipment allocation per site while meeting availability targets — confirming a differentiated requirement between the primary base and secondary locations. Most significantly, the analysis revealed that inspection frequencies could be reduced by 25% across three to four sites without degrading equipment readiness. Key outcomes included:

• 25% reduction in inspection requirements validated across multiple sites
• Differentiated equipment requirements quantified per site, enabling right-sized fleet allocation
• Shift from assumption-based to model-validated maintenance planning
• Planners gained a reusable simulation tool for ongoing scenario analysis as fleet or site conditions change

• Discrete-event simulation is well-suited to multi-site mining operations where equipment availability is sensitive to both fleet size and maintenance cadence — model before committing to operational changes.
• Over-inspection is common and addressable; a 25% reduction in inspection requirements achieved here suggests many operations carry hidden maintenance overhead that simulation can quantify.
• Capturing every maintenance activity type, duration, and frequency is prerequisite work — the accuracy of a digital twin depends entirely on the completeness of its maintenance data inputs.
• Differentiated fleet requirements across sites are often invisible until modeled — avoid applying a single allocation standard to sites with different operational profiles.
• Digital twin tools built for simulation (not just visualization) produce actionable scheduling guidance, not just dashboards.