Africa hosts about 30% of the world’s total mineral reserves and a higher share of diamonds, vanadium, manganese, platinum, cobalt and gold deposits. However, unlocking the true potential of the continent’s metals and minerals industry also hinges upon the ability to efficiently move product from the mine to the customer.

Ceenex has extensive experience in the field of mining logistics. This learning has been deployed on many successful flagship mining projects in South Africa and in other countries on the continent on behalf of leading Engineer, Procure, Construct and Manage (EPCM) contractors. Among these are the successful completion of cutting-edge simulations of mining logistics from pit to ship via barge transshipment during the projects’ Pre-Feasibility and Feasibility phases.

These simulations identify where exactly the bottleneck is in the entire system and whether throughput targets can be met on time and at minimal cost.

They also help to determine the optimal run-of-mine stockpile size to effectively buffer mining plant production. By being able to ascertain the tip bin capacity and conveyor feed rate, it is also possible to buffer the feed conveyor from truck tipping.

Moreover, the modelling can determine the number and capacities of plant modules that are required for the project, as well as product stockpile size to effectively buffer transport to port from plant production.

Our simulations also help to verify the number and capacity of trucks and trains that are required to transport the required tonnes at the lowest cost and least risk. This is in addition to determining the required port stockpile size to effectively buffer barge loading from overland transport.

Moreover, the ability to determine the ideal loading rate enables the optimisation of the number and capacity of tugboats and barges, as well as their loading processes.

The simulations also facilitate an improved understanding of the minimum vessel loading rate for a specific barge configuration to improve vessel loading rates.

Notably, they have also helped to develop operating philosophies for those operations that interact and have an impact on the entire throughput rate of the system.

From mine to ship

Simulating mine operations and all the components of the system through to the loading of vessels at sea is an extensive undertaking.

This includes the logistics involved in moving product from the mine to the stockpile; the run-of-mine stockpile levels; throughput as product to waste split and yield; as well as product stockpile levels. Stockpile loading for road or rail transport to port;

overland traffic en route to port and offloading at the facility, as well as the loading of vessels or branches at multiple quays are also modelled. This is in addition to the potential impact of tides on loading and sailing times, which includes simulating port infrastructure constraints, as well as transshipment from barge to vessel and loading of the ship at sea.

The modelling of opencast or underground operations are based on mine plans, and includes simulating variations in quality and yield, as well as throughput, which is also gleaned from equipment quantities and capabilities; seasonal differences, such as rain and mist; scheduled maintenance; and breakdowns.

Based on the mine layout over life of mine, Ceenex’s simulations of the logistics involved in moving product from the mine to stockpile even include varying numbers of trucks of different capacities and speeds.

This is in addition to the many types of stockpile reclaiming methods deployed in the different types of offloading processes at African port facilities. These may span the feeding of hoppers with front-end loaders through to the use of various types of automatic reclaimer systems.

We are also able to simulate front-end-loading operations deployed to stockpile the product, stacker-reclaimer movements and conveyors at the port to determine potential constraints.

The models of transshipment from barge to vessel are just as detailed. They include the number and various sizes of barges required to efficiently transship product to the vessel. This is in addition to the number and availability of tugboats at the port, as well as traffic in narrow sections of rivers. 

Simulation of vessel loading at sea include the impact of wind, in addition to wave frequency and amplitude, as well as the many variables that are usually encountered during vessel arrival times.

Total cost, risk and value of ownership

These cutting-edge simulations continue to assist project teams in ascertaining the total cost of ownership of the system by achieving throughput with minimal demurrage. This is based on a thorough understanding that the simulations provide of the actual versus planned throughput of the mine and demurrage of vessels.

They also assist in determining total risk of ownership that is expressed as the width of the delivery probability distribution.

This is in addition to helping to ascertain the total value of ownership of the project. It is expressed as the value added by each scenario over-and-above the cost, including non-tangible value, such as customer satisfaction, as well as environmental and community impact, dust and noise.

These key-performance indicators were also demonstrated on a simulation that Ceenex undertook of a mine, railway line and port facility for a large coal project in Mozambique.

The project aimed to mine and transport 11-million tonnes of coal via rail through the Port of Beira. Infrastructure to be developed at the facility included a rail yard and tippling facility; a stockyard with an automated stacker/reclaimer; and a single berth with a barge loader. Considering the depth of the port, ships had to load offshore at anchorage with floating cranes and barges.

Our simulation assisted the project team in evaluating the capacity of the system, influencing design decisions, as well as assessing tender feasibility and cost. 

The study was able to verify the capacity of the system to transship the required tonnage from the tip to the ship. This is considering the constraints of mining and plant production, railway, stockyard layout and capacity, as well as transshipment operations.

Our modelling also explored various ways of reducing the required stockyard size and throughput, while helping to develop a total cost of ownership model to evaluate the cost and risk of each transhipment tender.

Determining bottlenecks in a complex logistical system

Our simulations provide an effective means of determining the bottlenecks, to which all decisions are subjected, in this complex logistical system.

A case in point is deciding whether to increase barge capacity when available loading time is constraining the system.

The decision to increase the number of barges so that there is always one available to load and ensuring that they are all accompanied by a tugboat with each tide needs to

be weighed against the increase in draft and corresponding increase in loading time. While optimising between quays, barge capacity, loading time and rate will increase throughput, it will come at a cost.

Therefore, the aim is to find a perfect balance between the number, capacity and loading rate, with additional options to increase the quays-side loading draft.

Deploying too many small barges will impact throughput due to the extensive docking and undocking time involved. At the same time, large barges increase the likelihood of missing a tide or prematurely stopping loading to make a tide.

The challenge is to have a fully loaded barge ready to sail by the time the tide is high enough without over-engineering barge size or loading rate. Generally, empty barges are unconstrained by tides.

Modelling different and seemingly impossible scenarios

Notably, these simulations also simplify the process of establishing different and seemingly impossible scenarios to ascertain the true limitations of the operation.

For example, they have demonstrated how increasing the number of loading and hauling equipment may not necessarily impact the overall system throughput when the mine is not the bottleneck.

The many pit-to-ship simulations that Ceenex has undertaken over the past decade have also shown that shift changes, when forced to take place at the same point in the cycle for all trucks and at the same time in a truck logistical system, can seriously impede productivity.

According to our simulations of various operations, shift changes and multiple shift change locations are sometimes a better alternative to increasing the number of trucks in the system. This is considering that the additional trucks usually just end up in queues at the start of each cycle.

Moreover, our models have demonstrated how demand-based refuelling of trucks using well-located refuel stations and queue management systems are also significantly more effective than schedule-based refuelling at an off-site depot.

However, the timing of the simulation in the project lifecycle is critical. If undertaken prematurely, data gathering is usually incomplete as many of the processes are yet to be designed and this leaves many assumptions.

When simulation is undertaken too late in the project lifecycle, breaking though bottlenecks is more complicated and costly as this may even entail major redesign of certain components in the system.

Ceenex looks forward to assisting you to optimise your pit-to-port projects.