01 / Specifications
Product specification compliance
Plan every product blend against its quality specification so fewer targets are missed across the planning horizon.
Customer case study · Coal
Coal Quality Consistency Optimisation Software
BlendOpt is a configurable optimisation platform for mining value chains. Configured for coal quality consistency, it plans stockpiling, CHPP processing and product blends so that every coal product is delivered within its quality specification, reducing off-spec product without changing the mining schedule.
Customer resultMulti-seam coal mine
Powered by BlendOpt
Outcome
35% → <5%
Share of targets violating product specifications across a five-year plan, against the previously existing plan.
Rejection limitsZero violations
Mining scheduleUnchanged
Plan horizonFive years
Coal · metallurgical & thermalCase study below
What BlendOpt optimises
What BlendOpt optimises for consistent coal quality
Specifications, stockpiles and the process plant are optimised together across the whole planning horizon, not one period at a time.
02 / Hard limits
Rejection limits as hard constraints
Treat quality limits that would cause a product to be rejected as hard constraints, and never trade them away for other targets.
03 / Stockpiles
Stockpiling strategy
Set stockpile definitions and stacking and reclaim decisions so the right coal is available to blend when a product needs it.
04 / CHPP
CHPP processing strategy
Choose how the CHPP processes each coal so product quality stays within a narrow specification.
05 / Blending
Blending from multiple seams and pits
Combine ROM coal from open pit and underground seams into metallurgical and thermal products with consistent quality.
06 / Fixed plans
Fixed mine schedules and sales volumes
Take the mining schedule and sales volumes as fixed inputs, and improve product quality through the stockpiling, processing and blending decisions downstream of ROM.
Customer results
Coal quality consistency results
Results BlendOpt customers have measured in coal product quality, stockpiles and blend scheduling.
35% → <5%
coal specification violations across a five-year plan, with zero violations of rejection limits
Read the coal consistency case study below →
+$24M / yr
forecast revenue from new stockpile definitions and a moderate capacity change at a coal operation
Stockpile optimisation case study →
within 0.6%
of the vessel COA for predicted coal qualities, while meeting contract requirements
Port blending and day-of-operations scheduling →
The whole value chain
Coal quality in the context of the whole value chain
Coal quality at the ship or the customer is set much earlier: by the ROM coal the mine schedule delivers, how it is stockpiled, how the CHPP processes it and how products are blended.
BlendOpt takes the mine schedule as an input and models stockpiles, the processing plant and product specifications together, so each downstream decision is judged by its effect on the products that are sold. See how this works for coal blending software, stockpile definition optimisation, train-to-vessel blend scheduling and integrated mine planning and scheduling.
Coal quality value chainFixed schedule. Consistent products.
BlendOpt model
- ROMopen pit & underground seams
- Stocksstacking & reclaim
- CHPPprocessing strategy
- Blendsproduct blends
- Productsmet & thermal specs
Optimisation objective
Every product within specification
Stockpiling, processing and blending decisions are optimised across the full plan, with rejection limits held as hard constraints.
Customer case study · Coal
Case study
Coal quality consistency
35% to under 5% coal specification violations across a five-year plan
An open pit and underground multi-seam coal mine used a BlendOpt digital twin to optimise stockpiling and CHPP processing strategies, delivering more consistent product quality without changing its mining schedule.
- ~35% → <5%of targets off specification
- 0rejection-limit violations
- Met & thermalcoal products
Customer outcomes
- Spec violations 35% to under 5%
- Zero violations of rejection limits
- Optimised five-year plan
01
The challenge
An open pit and underground multi-seam mine sold several metallurgical coal and thermal coal products. There was a particular quality attribute that was sometimes difficult to control in product blends but that was important to buyers. The mine’s parent company engaged Paradyn to determine if a more consistent product quality could be achieved through optimised stockpiling and CHPP processing strategies without making changes to the mining schedule, which was constrained and had limited optionality due to the layout of the underground mine.
The planning problem was defined such that sales volumes for each product were fixed, so opportunities for improvement were not in relation to production yields or margin and instead related to the delivery of products within a narrow quality specification.
02
The solution
BlendOpt was used to construct a digital twin of the customer’s operation using a combination of stockpile definitions, process plant and product specifications that reflected the customer’s operational reality.
03
The value unlocked
The BlendOpt optimiser demonstrated its value as an effective coal supply management software application, and discovered plans that violate product specifications in <5% of targets in comparison to a previously existing plan that violated specifications in ~35% of targets across a five-year plan. Importantly, BlendOpt did not violate any quality specifications that were rejection limits, i.e. hard constraints for product sale.
FAQ
Coal quality consistency optimisation FAQ
How BlendOpt keeps coal products within specification through stockpiling, CHPP processing and blending.
What is coal quality consistency optimisation?
Coal quality consistency optimisation is planning how coal is stockpiled, processed and blended so that each product is delivered within its quality specification, period after period. The aim is to reduce off-spec product rather than to change production volumes. BlendOpt does this by optimising stockpiles, the CHPP and product blends together across the whole planning horizon.
Can coal quality consistency be improved without changing the mining schedule?
Yes. BlendOpt takes the mining schedule as an input. In this case study it was constrained with limited optionality because of the underground mine layout, and it was left unchanged. BlendOpt improved product consistency through optimised stockpiling and CHPP processing strategies instead, cutting specification violations from about 35% of targets to under 5% across a five-year plan.
What is the difference between a quality target and a rejection limit?
A quality target is a specification the buyer wants the product to meet, and missing it may reduce the product's value. A rejection limit is a hard constraint for sale: if it is breached, the product can be rejected. BlendOpt treats rejection limits as hard constraints, and in this case study its plan did not violate any of them.
How does BlendOpt reduce off-spec coal product?
BlendOpt builds a digital twin of the operation from its stockpile definitions, process plant and product specifications. The optimiser then searches for stockpiling, processing and blending decisions that keep each product within specification across the full plan, rather than correcting quality one period at a time. At a South African coal exporter, predicted qualities were within 0.6% of the vessel COA while meeting contract requirements.
Does BlendOpt support both metallurgical and thermal coal?
Yes. The mine in this case study sold several metallurgical coal and thermal coal products, and BlendOpt optimised the stockpiling and CHPP strategy behind all of them. The same approach applies to coal blending and stockpile planning more broadly, where one coal operation added a forecast $24M a year in revenue from new stockpile definitions and a moderate capacity change.