Getting a model built can be a painful experience, but it doesn’t need to be that way. At Simulus Engineers our vision is to simplify and speed up the whole process by making the most of our experience and our passion for efficiency.
We offer a library of standard, verified model blocks that can be readily assembled and customised to your specific project. All metallurgical processes can be accommodated on either a steady state or dynamic basis.
We’re confident enough to offer a fixed price package for most modelling applications. Our customers know exactly what they’re getting and exactly what it costs. As always, our approach is open and transparent so the client has full access to the model to scrutinise, verify and use as they choose.
Process simulation provides the critical link from data to decisions. Simulus builds models which demystify the behaviour of complex systems and uncover the information needed for informed business decisions.
Our simulation engineers are focussed and skilled in making the best use of the available technology. The cornerstones of our approach to model development are:
- The right tools – there is a wide range of simulation software to choose from. We take an independent stance and adapt to specific client and project requirements.
- Systems based – A methodical, disciplined approach helps minimise errors, avoid repetition, and give the overall shortest path to completion.
- The team approach – Process simulation is a specialised skill, but should not be seen as an isolated task. The model is central to the process design and the engineer building it gains an intimate understanding of how the process behaves. Simulus stresses the need for modelling to be closely integrated with metallurgical testing, process design, cost estimation and other related tasks.
Simulus models fall into three broad categories:
- Steady state
- Dynamic – plant level
- Dynamic – enterprise wide
Steady state simulation
The fundamental model of a continuous process flowsheet is the steady state mass and energy balance. All information about material and energy flows, stream composition, chemical reactions, and physical separations is combined into a single model. The model generates flow, temperature, pressure and composition, on a stream by stream basis.
The balance feeds into all facets of plant design:
- Line sizing
- Equipment sizing
- Material selection
- Reagent consumption
- Utility requirements
- Environmental emissions
Dynamic models – Plant level
Dynamic models account for the key economic drivers over time, and show the real variability that occurs through mining, processing and transportation operations.
A plant level dynamic model applies discrete events and dynamic constraints to a flowsheet mass and energy balance. Models are customised to each site, but normally include data such as:
- Ore grade and tonnage profile
- Equipment throughput capacity
- Equipment failure statistics
- Planned maintenance schedules
- Storage and surge capacity
- Utility and reagent supply limitations
Model outputs mimic the real production data of interest to the operation, such as tonnes processed, plant utilisation and delay times.
The main purpose is to determine the likely realistic production rate of a process, and to support key functions in plant design:
- Optimising the surge capacity and throughput rates in each area
- Identifying key process bottlenecks
- Evaluating, debottlenecking or expansion scenarios
Area throughput rates and surge tank levels are tracked and plotted over time. By examining the output data one can answer questions such as:
- Are the surge/storage vessels big enough/too big?
- Which equipment or area is frequently holding up the process?
- Which equipment or area is being under-utilised?
- Is the reagent/utility supply ever a limitation?
- Where is standby equipment justified?
- Are parallel trains better than a single train?
The model ultimately helps find the most cost effective way to maximise production.
Dynamic models – Enterprise level – Production and supply chain logistics
Dynamic models can be used to simulate an entire operation from the mine to the final customer. The processes are typically a combination of continuous and discrete event operations. The most common application is production and supply chain logistics for bulk commodities such as coal and iron ore. Operations include:
- Stockpiling and reclaiming
- Ore/product blending
- Rail transportation
- Port operations
An enterprise level model ultimately tracks the entire process from mine to market. The tension between customer demand and mine supply, impact on stockpile levels, product blending requirements, and transportation constraints are all treated in a single supply chain model. The model outputs help to answer questions such as:
- Where are the true bottlenecks?
- What happens when a new mine comes on line?
- What impact will we see from:
- Increasing the trucking fleet?
- Installing passing loops in the rail system?
- Increasing conveyor capacity?
- Increasing stockpile capacity?
- How do we minimise ship wait times?
- How fast can we meet customer demands for product specifications?
A visual display shows truck/train/ship movements, stockpile levels, and other key indicators.