2.3. Decision on Production Cost

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 scenario, the focus is on using 5 scrapers. This number is below the ideal requirement. When you have fewer scrapers than necessary, they become more critical to production since they control the workflow. The pusher, on the other hand, has an easier job as it waits for the scrapers. If scrapers are not available, the pusher cannot operate effectively as it relies on them to do its job. This situation creates a bottleneck where the scrapers dictate the pace of production.

Think of a restaurant with limited cooks (scrapers) and waiters (pushers). If there are too few cooks, they can't prepare meals fast enough, causing wait times for diners. Meanwhile, the waiters are just standing by, unable to take new orders until meals are ready. Hence, the cook's number is critical for efficient service.

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) 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

To determine the actual productivity of the scrapers, we use the volume each scraper can handle. Here, each scraper can manage 19.82 bank cubic meters. We then multiply this by the number of scrapers (5) and adjust for the time taken to complete a cycle. The cycle time of each scraper is 7.78 minutes, so we calculate how many of these cycles fit in an hour (working at 50 minutes an hour against total time). The result gives us a production rate of 636.89 bank cubic meters per hour.

Imagine a bus carrying students. Each bus can hold 20 students (equivalent to volume per load). If you have 5 buses, you can transport a total of 100 students per trip. However, if each trip takes 30 minutes and the buses can only operate for 50 minutes in an hour, you need to calculate how many trips can be completed within that timeframe to understand your 'student transport capacity'.

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.

When the number of scrapers exceeds the ideal balance, the situation changes significantly. In this case, scrapers are not the limiting factor; instead, they end up waiting for the pusher to be ready. This means that the pusher’s cycle time now becomes the crucial aspect of production flow. If the pusher is not available, the entire operation can stall since the scrapers can work faster than they are being utilized.

Consider a library where you have too many librarians (scrapers) but not enough library clerks to check in books (pushers). The librarians can organize many more books than can be processed, leading to a backlog where librarians are idle while waiting for clerks to be available to take the books off their hands.

We need the unit production cost in terms of the cost per bank meter cube. That is why we have to estimate the production also in the bank cubic meter. So, it is already estimated earlier the volume per load that is a volume of the bowl is 19.82 bank cubic meter.

To assess which configuration of scrapers and pushers offers the best financial outcome, we need to calculate the unit cost of production. This involves determining how much it costs to produce one bank cubic meter of material. We previously figured that our scrapers can handle 19.82 bank cubic meters per load, and we will consider how many loads are produced to derive a cost per cubic meter produced, which allows for comparison between different operational setups.

It’s like running a bakery. If a batch of cookies costs $5 to make and produces 20 cookies, then each cookie effectively costs$0.25. If you can find ways to reduce that cost, such as buying ingredients in bulk or streamlining your baking process, that affects how profitable each cookie can be when sold.

Now let us estimate the cost. How to calculate the unit production cost? Total unit cost of production for combination Cost of Push tractor with operator Cost of scraper with operator + ×number of scrapers)

To calculate the total unit production cost, we consider the costs associated with both the pusher and scrapers, including their operational costs. We factor in the quantity of scrapers used in combination with a single pusher. This computation helps identify which option results in lower production costs per bank cubic meter, which is essential for businesses looking to minimize expenses while maximizing productivity.

Think of running a delivery service. You need to account for the costs of your delivery vehicles and drivers (pushers) as well as what it costs to maintain your product delivery (scrapers). If one delivery method costs more than another for the same distance, you’d choose the lower-cost option to maximize your profitability.

So, we have come to the end of this lecture. The solution is we are going for 5 scrapers and 1 pusher. The associated production value is 636.89 bank cubic meter per hour and the unit production cost associated is rupees 44.12 per bank cubic meter.

We conclude that using 5 scrapers with 1 pusher optimally balances productivity and cost. The production rate achieved is 636.89 bank cubic meters per hour, with a unit production cost of ₹44.12 per bank cubic meter. This method not only enhances efficiency but also keeps costs managed, which is crucial for project budgeting and planning.

It’s similar to figuring out how many workers are needed in a factory. If 5 workers can produce 100 widgets per hour at a $2 cost per widget, whereas 6 workers might only produce 120 widgets at a$2.50 cost per widget, it illustrates clearly when it makes more sense to operate with fewer but more efficient workers.

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