Supply Chain Analytics - Business Analytics
Budget: ₹600 – ₹1,500 INR
you are still working at Smart Consultants Pvt Ltd. and one of your clients that handles an open-pit mine comes to you saying that they are facing a problem of low production at the mine. This is an indication of the low efficiency of the mine operations and is also causing higher management to increase the cost of production.
Although the mine is in continuous operation, it is taking longer to serve the requirements of the customers. This is, in turn, causing distress among the customers, which is, in a way, reducing your market value and is also forcing your customers to send requirements to other open-pit mines. But this time, your client does not ask you to conduct a root cause analysis of the problem that they are facing. They explicitly tell you that there is a problem with the queues at each digger and crusher, to the extent they are not optimised. The client currently functions without an artificial intelligence solution.
Instead, available trucks are assigned to diggers and crushers randomly on the field. Ideally, the truck assignment should have been considered using the distance between each digger and crusher, and the truck travel time. And the assignment should also have been considered, i.e. which trucks at diggers and crushers go empty in the next few cycles. Your client asks you to build an optimisation model. If you manage to achieve a matching factor of 900+ for a truck and a digger, and a matching factor of 300+ for a truck and a crusher, then the operational cost would reduce by almost 50% and it will save a large amount of money for the higher management.
Let's understand more about the problem and what matching factor exactly is in the next few segments.
After drilling and blasting are completed, diggers excavate the mined ores, where they start the crowding operations, i.e., gathering the ore into stockpiles. This ore is then are loaded into dump trucks, which take these ores back to the crusher sites where they are crushed into granular pieces. The empty trucks go back to the digger sites to collect additional ore.
If empty trucks are not queued at the digger sites, then the digger operation will have to stop until the next empty truck arrives. Similarly, if there is no loaded truck at the crusher site, the crusher operation is stopped until a loaded truck arrives and dumps additional ore. Thus, in a typical scenario, it is essential to ensure that sufficient trucks are assigned at diggers and crushers so that their operations are running smoothly. This will ensure that continuous production is maintained and is maintained at a certain rate.
So, in the Truck Cycle, we looked at the cyclic movement, wherein an empty truck lined up at a digger (Waiting Stage) is first parked at the Loading position (Spotting), where it gets loaded by the digger. After the truck is loaded at the digger, it drives away from the digger and moves to the crusher. This process is called Hauling. Here, it is called hauling because it carries a load to the crusher. At the crusher, the truck is again queued, waiting for its turn.
As soon as its turn comes, it backs into the crusher which is called Backing and at this position, it would offload the ore into the crusher and this is called Tipping. After this, the truck becomes empty and heads back to wait for loading at a digger (Travelling). This cycle from Waiting, Spotting, Loading, Hauling, Backing, Tipping, Travelling and back to Waiting is called the Truck Cycle.
Similarly, diggers also operate in a cyclic manner. Each digger has a swing arm, which carries the load in a clockwise direction in order to gather the ore and add to the stockpile. This is called Crowding. Next, the digger would place the bucket load, which is called Load, into a truck. This requires multiple cycles to load the truck while using buckets to load.
we will look at what queue theory is.
for more info please reach me out
Although the mine is in continuous operation, it is taking longer to serve the requirements of the customers. This is, in turn, causing distress among the customers, which is, in a way, reducing your market value and is also forcing your customers to send requirements to other open-pit mines. But this time, your client does not ask you to conduct a root cause analysis of the problem that they are facing. They explicitly tell you that there is a problem with the queues at each digger and crusher, to the extent they are not optimised. The client currently functions without an artificial intelligence solution.
Instead, available trucks are assigned to diggers and crushers randomly on the field. Ideally, the truck assignment should have been considered using the distance between each digger and crusher, and the truck travel time. And the assignment should also have been considered, i.e. which trucks at diggers and crushers go empty in the next few cycles. Your client asks you to build an optimisation model. If you manage to achieve a matching factor of 900+ for a truck and a digger, and a matching factor of 300+ for a truck and a crusher, then the operational cost would reduce by almost 50% and it will save a large amount of money for the higher management.
Let's understand more about the problem and what matching factor exactly is in the next few segments.
After drilling and blasting are completed, diggers excavate the mined ores, where they start the crowding operations, i.e., gathering the ore into stockpiles. This ore is then are loaded into dump trucks, which take these ores back to the crusher sites where they are crushed into granular pieces. The empty trucks go back to the digger sites to collect additional ore.
If empty trucks are not queued at the digger sites, then the digger operation will have to stop until the next empty truck arrives. Similarly, if there is no loaded truck at the crusher site, the crusher operation is stopped until a loaded truck arrives and dumps additional ore. Thus, in a typical scenario, it is essential to ensure that sufficient trucks are assigned at diggers and crushers so that their operations are running smoothly. This will ensure that continuous production is maintained and is maintained at a certain rate.
So, in the Truck Cycle, we looked at the cyclic movement, wherein an empty truck lined up at a digger (Waiting Stage) is first parked at the Loading position (Spotting), where it gets loaded by the digger. After the truck is loaded at the digger, it drives away from the digger and moves to the crusher. This process is called Hauling. Here, it is called hauling because it carries a load to the crusher. At the crusher, the truck is again queued, waiting for its turn.
As soon as its turn comes, it backs into the crusher which is called Backing and at this position, it would offload the ore into the crusher and this is called Tipping. After this, the truck becomes empty and heads back to wait for loading at a digger (Travelling). This cycle from Waiting, Spotting, Loading, Hauling, Backing, Tipping, Travelling and back to Waiting is called the Truck Cycle.
Similarly, diggers also operate in a cyclic manner. Each digger has a swing arm, which carries the load in a clockwise direction in order to gather the ore and add to the stockpile. This is called Crowding. Next, the digger would place the bucket load, which is called Load, into a truck. This requires multiple cycles to load the truck while using buckets to load.
we will look at what queue theory is.
for more info please reach me out