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Today, we’ll discuss how to estimate production costs using scrapers and pushers. Does anyone know why it's important to balance the number of scrapers and pushers in a project?
Is it to ensure everything runs smoothly without any waiting time?
Exactly! If we have too few scrapers, the pushers will have to wait. If we have too many, the scrapers will wait. Let's break down the calculation for the productivity with 5 scrapers.
How do we calculate productivity?
"We multiply the number of scrapers by the volume per load and factor in the cycle time. The formula is:
Now that we understand productivity, let’s estimate unit production costs. Can anyone tell me how it’s calculated?
Is it the total cost divided by productivity?
Yes! We take the total hourly costs of scrapers and pushers and divide them by the productivity per hour. For instance, can someone calculate it for 5 scrapers?
If the pusher costs ₹5600/hr and each scraper costs ₹4500/hr, then for 5 scrapers it’s ₹5600 + (₹4500 x 5) = ₹26600.
Excellent! Now, dividing by 636.89 bcm/hr gives us a cost of ₹44.12 per bcm.
What about increasing the number to 6 scrapers?
Great point! For 6 scrapers, checking the costs, we find that the unit cost goes up slightly to ₹45.07 per bcm. This demonstrates balancing productivity with cost efficiency.
Let’s analyze what happens if we exceed the optimal number of scrapers, say using 7 scrapers instead of 5 or 6.
Does that mean scrapers will be waiting for the pusher?
Exactly! In this scenario, the pusher becomes the critical element. Can anyone tell me how to estimate productivity in this case?
We’ll focus on the pusher's cycle time instead, right?
Correct! When pushers control production due to idling scrapers, we’ll compute based on the pusher’s efficiency. Always remember, balancing these components impacts overall project efficiency.
Productivity is determined by the number of scrapers and their cycle times relative to the workload.
Costs are calculated based on the total operational costs divided by productivity, indicating efficiency.
Optimal production occurs when the number of scrapers is balanced with the capacity of pushers, preventing idle time.
If 5 scrapers produce 636.89 bcm/hr at a cost of ₹44.12 per bcm, and 6 scrapers produce 723.36 bcm/hr at a cost of ₹45.07 per bcm, there's an evident trade-off between productivity and cost.
Switching to 7 scrapers shifts the production control to the pusher, requiring a focus on pusher efficiency for cost-effective operations.
Cost and time, in construction game; Balance the scrapers, avoid the blame.
Imagine a busy construction site with too many scrapers waiting for pushers. One day, they realized their cost efficiencies by balancing machine numbers, leading to a well-oiled operation.
P.C.S. - Productivity, Costs, Scrapers: Remember that impactful production requires balance in these three.
BOSP - Balance Of Scrapers and Pushers for optimal production.
Term
Unit Production Cost
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Term
Productivity
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The cost incurred per unit of production, typically expressed in terms of cost per bank cubic meter in construction contexts.
The total time taken for an entire operational cycle of a machine, including loading, transporting, and unloading.
The quantity of material produced per unit of time, often measured in bank cubic meters per hour.
The effective operational time used by machinery in relation to its total operational time, represented as a percentage.
This section discusses how to estimate unit production costs and the factors influencing the number of scrapers and pushers needed for an efficient operation.
The section covers the concept of estimating production based on the number of scrapers used relative to a pusher, including calculations of productivity and unit costs for various configurations. It explains the implications of using fewer or greater numbers of scrapers than ideal and how to achieve optimal costs.
This section provides a comprehensive overview of how to calculate unit production costs for scrapers and pushers in construction projects. It begins with the scenario of using five scrapers, emphasizing that fewer scrapers than needed results in production being controlled by the available scrapers, while additional pushers wait idly. The productivity is calculated based on the number of scrapers, the volume per load they handle, and their cycle times.
The discussion further delves into unit costs, assessing cost factors like the hourly rates of pushers and scrapers, resulting in specific unit costs for different configurations. For instance, 5 scrapers yield a lower unit cost of ₹44.12 per bank cubic meter compared to ₹45.07 for 6 scrapers.
In conclusion, the section emphasizes the balance of productivity versus cost efficiency by choosing the right number of scrapers relative to pushers, ultimately guiding operational decisions in construction economics.