5.1. Summary of Productivity Estimation

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.

This chunk explains the impact of having fewer scrapers than needed for a task. When there are fewer scrapers (in this example, 5), they are in higher demand, and their availability controls the workflow. The pusher, which supports the scrapers, is underutilized because it must wait for the scrapers to be free before it can do its job. Thus, it's crucial to find the right balance in the number of scrapers and pushers to optimize overall production.

Imagine a busy restaurant kitchen where there are only two chefs (scrapers) and four servers (pushers). If there are only two chefs, they will be overwhelmed with orders, making the servers wait. However, if there are more chefs, the servers can keep serving dishes without delays. This analogy shows that having the right number of chefs (scrapers) affects the restaurant's efficiency.

So, here the scraper will be controlling the production as a scraper is a lesser in number, but the pusher will have the ideal time. So, now, let us see the productivity 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. Production (Scraper controlling) Efficiency, hr = (volume per load × no. of scrapers) / (cycle time of scraper, min) * (job efficiency, min/hr) =... 636.89 bcm/hr.

This chunk outlines how to calculate the production capability of the scrapers when using 5 units. The formula includes the volume of material the scraper can hold, the number of scrapers, and the time each takes to complete their cycle. The resulting figure indicates how much material can be moved per hour – here, 636.89 bank cubic meters per hour. This calculation ensures that the proper amount of production is recognized, which is essential for project planning.

Consider a large conveyor belt that can move 19.82 cubic meters of garbage per load. If you have 5 trucks (scrapers) loading garbage, and each truck takes about 7.78 minutes to complete a load while working effectively for 50 minutes in an hour, you can estimate how much garbage can be moved in an hour using the formula provided.

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. So, the scraper will be waiting for the pusher. Pusher is critical here.

This chunk discusses the opposite scenario, where there are more scrapers than the balance number needed for operation. In this case, the scrapers may not be working at full capacity because they are waiting on the pusher to be available to continue operations. Here, the pusher determines the pace of production since scrapers have idle time waiting for their counterpart to transport the load.

Imagine a factory assembly line where each workstation is a separate task – for example, packing items, labeling, and stamping them. If there are too many workers at the labeling station but not enough at the packing station, the labeling workers will be idle while they wait for items to be packed. Therefore, the packing station (pusher) controls the speed of the entire line.

Based on productivity if I select obviously I have to go for 6 number of scrapers per pusher, because 5 scrapers is giving you 636.89, 6 scrapers is giving you 723.36 bank cubic meters per hour. So, obviously 6 scrapers per pusher is giving you higher productivity.

This chunk highlights the decision-making process regarding the number of scrapers selected based on their productivity. By analyzing the hourly production rates of both 5 and 6 scrapers, it becomes evident that 6 scrapers yield more material movement per hour (723.36 bank cubic meters), which would be the preferable choice if productivity is the primary concern.

Think of a delivery team using bicycles. If one team has 5 bicycles and completes 636 deliveries in an hour, while another team with 6 bicycles can manage 723 deliveries, the more bicycles provide better productivity. Businesses often opt for more resources if it means getting more work done efficiently.

Let us now estimate the cost. How to calculate the unit production cost? Total unit cost of production for combination = [Cost of Pusher tractor with operator + Cost of scraper with operator × no. of scrapers] / Job production. So, it is nothing but you hourly cost by hourly productivity.

This chunk explains how to estimate unit production costs by taking into account both operational and ownership costs and dividing that total by how much productivity is generated per hour. It emphasizes the importance of factoring in all costs associated with machinery when evaluating different productivity levels, which helps make good business decisions regarding equipment and labor use.

Imagine you run a lemonade stand. You spend $20 on ingredients, cups, and a small stand setup, which allows you to sell 100 lemonades. To find out how much each cup costs you in production, you’d divide your total costs ($20) by your total output (100 cups), calculating a unit cost of $0.20 per lemonade.

So, if you are concerned more about your production cost only in that case most of the cases people are concerned only about minimizing the production cost. So, in that case we have to go for the combination which gives you the minimum unit production cost.

This final chunk focuses on the decision-making aspect where cost is prioritized over productivity against time pressures. The conclusion drawn from the earlier productivity calculations is that it’s often wiser in construction projects to select machinery configurations that minimize costs even if they don't maximize output.

In managing a household, consider whether to buy a larger, more expensive washing machine that cleans clothes faster versus a smaller, cheaper model that takes longer. If your focus is strictly on saving money, you might choose the smaller model even if it requires more time to complete the task.

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