3.3. Correlating Rimpull with Horsepower

Now, let us consider the economics of going for 5 scrapers. So, 5 in the sense you are going to use lesser than what is needed, you are assuming 5 that means you are going to use the number of scrapers lesser than what is needed. So, when the number of scrapers are lesser than the balanced number so obviously scrapers are more critical, but a pusher will have the ideal time. Your pusher will wait for the scraper.

In this section, we first need to understand the impact of using an inadequate number of scrapers, which is less than what is considered optimal (or the balanced number). When you have fewer scrapers, these machines become critical in the workflow—they control production because they directly dictate how quickly material can be moved. In contrast, the pusher, which supports the scraper, will often be idle because it cannot operate without the scraper being ready to do its job. This imbalance can lead to inefficiencies, as the pusher waits for the scraper to catch up.

Imagine a relay race where one runner consistently trips or is slower than the others. The baton (or load) waits for this slower runner, causing delays for the whole team. Similarly, in this scenario, the pusher (like the other athletes) can’t keep moving efficiently because the scraper is not ready with the load.

So, now, let us see the productivity in this case of n equal to 5 scrapers. How to estimate the production of this scraper? The volume of your bowl volume per load, you know the value of 19.82 bank cubic meter.

Now that we have established the critical nature of the scrapers, we move on to calculating their productivity. For five scrapers, we look at the bowl volume of each scraper, which is given as 19.82 bank cubic meters. This volume is crucial for understanding how much material each scraper can carry per load. To estimate total productivity, we need to factor in the number of scrapers, the volume each can carry, and the cycle time required to complete one loading operation.

Think of a school bus making trips to carry students to a field trip. If the bus can hold 19.82 students per trip and you have five such buses, the total number of students moved in one trip would be 5 x 19.82. Similarly, here every scraper's limit adds to the overall productivity.

Production (Scraper controlling) min Efficiency, hr = ×no. of scrapers ×vol. per load Cycle time of scraper, min 50 min/hr = ×5 ×19.82 bcm = 636.89 bcm/hr 7.78 min.

Now we apply a formula to derive the hourly production rate of the scrapers. Assume a cycle time of 7.78 minutes for loading. By converting the cycle time to hours, along with considering that in an hour, the scrapers effectively work for 50 minutes due to efficiency losses, we can calculate the production output. Multiplying the number of scrapers (5) with the volume per load (19.82 bank cubic meters), we divide by the total cycle time (converted to hours) to get 636.89 bank cubic meters per hour as the productivity of 5 scrapers.

Just as a factory can produce a specific number of products every hour based on how many machines (or workers) are in operation and how long it takes for each to complete a task, here, we’re calculating how much material can be processed per hour based on the scrapers' capacities and cycle times.

If n is greater than the balance number that means you are going to use more number of scrapers, then what is indicated by the balance number. In this case, scrapers will have the ideal time. Scrapers are not critical.

Moving forward, when the number of scrapers exceeds the balanced number—meaning we have more than what is optimal—the situation changes. The additional scrapers won't improve productivity as they might experience idle time waiting for the pusher to clear the load. Here, the pusher becomes the critical component. It is this machine that will dictate production flow since it now has to keep up with more scrapers. Therefore, the cycle time of the pusher is vital to maintain efficient operations.

Think of a busy restaurant kitchen. If you have a surplus of chefs but only one oven, the chefs may stand around waiting for their turn to cook rather than being productive. The oven (like the pusher) becomes the bottleneck in the workflow.

In this case pusher will be controlling the production. Pusher cycle time is critical. So, unless a pusher is available, I cannot complete my job.

This portion emphasizes the role of the pusher when there are excess scrapers. The pusher's cycle time, or the time it takes to do its task, becomes pivotal in determining overall production capacity. If the pusher cannot keep up with the increased number of scrapers, production halts. Thus, if we want to increase productivity further, it is necessary to assess whether we need to adjust not just the number of scrapers, but also ensure that the pusher can handle the workload.

Consider a concert where there are many musicians but only one sound engineer. If the engineer can’t manage all the instruments, the performance will suffer. The engineer, like the pusher, must efficiently manage all the inputs to deliver excellent results.

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