Optimising copper smelting with predictive simulation
Project facts
- Client
- Sinomine Tsumeb Smelter
- Location
- Namibia
- Challenge
- Bringing together the production and logistics departments to work in unison, rather than silos
- Solution
- A simulation model which integrated logistics planning and production needs with real time feedback
- Impact
- The simulaton model reduced downtime and ensured a more stable production flow, enabling Sinomine to meet delivery commitments in the most efficient way
To tackle these obstacles, Twinn's reseller partner in South Africa, Business Science Corporation (BSC) and their Productivity Science division, collaborated with Sinomine to implement a predictive simulation solution. This partnership, led by Sean Mowatt, Bryan Moore, and the smelter's metallurgist Dina Tiets, transformed what was once a manual, Excel-driven process into an integrated and dynamic planning tool that has reshaped day-to-day operations.
The challenge
Bridging the Gap Between Logistics and Production
Sinomine’s copper smelting process relies heavily on the timely delivery of copper concentrates from various locations to its production facilities. However, as Bryan Moore explained, the production and logistics departments were previously working in silos, each following separate planning methods. The logistics team focused on getting material to the plant, while production planned its processes assuming the material would be there on time. When delays occurred, production was left scrambling.As Bryan noted, "it's essential to stay aware of material supply timelines, as they play a crucial role in keeping production running smoothly through the course of the plan and beyond. The simulation tool actually predicts—given the logistics plan—whether production can proceed as expected." This prediction capability was a major turning point for Sinomine, allowing the smelter to plan holistically across the value chain rather than in isolation.
The solution
Predictive Simulation with Witness
The core of the solution was a predictive simulation model developed using Witness, a powerful tool for logistics and production planning. In less than six weeks, BSC developed a model that allowed Sinomine’s logistics and production teams to visualise and simulate the entire copper processing journey—from concentrate arrival at Walvis Bay to stockpiling, smelting, and dispatching the final product.
The Witness model simulates the whole logistics and production value chain
This simulation model integrated logistics planning with production needs, providing real-time feedback on potential bottlenecks or material shortages before they could disrupt operations. As Dina Tiets described, "Before using the simulation model, we had no real-time overview of concentrate movements. Now, we know exactly when shipments are arriving and can adjust our production plans accordingly."
One of the standout features of the simulation was its ability to force collaboration between previously siloed departments. “Now,” Bryan explained, “planning can go and run their plan, see that there’s a problem, and collaborate with logistics to adjust either the plan or the material delivery schedule.” This capability empowered the teams to make informed decisions before issues arose, fostering a new level of operational synergy.
The input screens used by the users at Tsumeb to set up their scenarios
The result
Reduced Planning Time and Increased Efficiency
The benefits of this predictive simulation were immediately measurable. For Sinomine, the time required for weekly production planning meetings dropped from three hours to just 20 minutes. The ability to visualise and adjust plans based on real-time data meant that logistics and production schedules were aligned, reducing costly downtime and ensuring a more stable production flow.
The results of the simulated scenarios provide the Tsumeb team with the necessary details to execute their plans with confidence
One particularly notable outcome was the impact on sulfuric acid production, a byproduct of the smelting process. With the simulation, the smelter could accurately forecast sulfuric acid output and ensure timely delivery to its customers. As Dina explained, "We model shipments and production together, so we know exactly when we can deliver sulfuric acid without exceeding our capacity or causing production to stop."
The Sinomine team have been using the simulation for more than four years now – a testament to the value they feel it provides them. “Our most successful implementations come down to three, equally important, factors – data, modeling, and people” Sean Mowatt explains. “Regardless of the technical sophistication of the solution, if it is not perceived to be easy to use while delivering real-world value, it will not be used sustainably. The inputs and guidance provided to us by the Sinomine team in setting up and enhancing the solution was, and continues to be, crucial to its longevity.”
The collaboration between BSC’s Productivity Science division and Sinomine Tsumeb Smelter highlights the power of predictive simulation in modern logistics and production planning. By integrating data from both departments and providing a unified platform for scenario analysis, BSC’s solution has helped Sinomine reduce costs, avoid production delays, and improve decision-making across the board.
As industries like mining and smelting continue to evolve, tools like the predictive simulation model implemented at Sinomine will play a crucial role in shaping the future of operational efficiency. Whether it’s reducing downtime, minimizing costs, or fostering greater collaboration between teams, the results speak for themselves: smarter planning leads to better outcomes.
