3.3. Importance of Accurate Cost Estimation

So, downtime cost per hour equal to 3% of your equipment cost. Equipment cost is nothing but 900 rupees per hour.

Downtime cost per hour = × (900) = 27 rupees per hour

Your machine is going to operate in a year for 2000 hours. So, what is your yearly downtime cost? Yearly downtime costs for the first year is,

Downtime cost per year = 27 × 2000 = 54,000 rupees.

To estimate the downtime cost of your equipment, you first determine its hourly cost, which is 900 rupees. The downtime cost represents the financial loss when the machine is not operational. In this case, downtime cost is calculated as a percentage of the equipment's cost. For example, if the downtime cost is 3%, the calculation shows that the downtime cost per hour is 27 rupees. When you multiply this by the total operating hours in a year (2000 hours), it results in a yearly downtime cost of 54,000 rupees.

Imagine you run a bakery that relies on an oven worth 900 rupees per hour. If the oven breaks down and you lose 3% of its value each hour it’s out of service, it costs you 27 rupees. For an entire year with 2000 working hours, this loss accumulates to 54,000 rupees. Just like a missed opportunity in your bakery leads to lost sales, downtime represents a significant loss in any business.

Similarly, calculate the downtime costs, let us calculate for the second year, in the second year the downtime percentage is 6%. So, downtime cost is 6% of your equipment cost,

Downtime cost per hour = × (900) = 54 rupees per hour.

Downtime cost per year = 54 × 2000 = 1,08,000 rupees.

In the second year, the downtime percentage increases to 6%. This means you need to recalculate the downtime cost, which is now 54 rupees per hour (6% of 900 rupees). To find the total downtime cost for the year, you again multiply the hourly cost by the total operational hours. This results in a substantial increase to 1,08,000 rupees for that year, highlighting how downtime costs can escalate over time.

Continuing with the bakery analogy, suppose your oven's malfunction becomes more frequent due to wear and tear, resulting in a downtime rate of 6% in the second year. This translates to a loss of 54 rupees per hour. If you operate 2000 hours, you end up with an annual loss of 1,08,000 rupees. Much like how a chef might start to lose more customers as the food production slows down, the growing downtime is a serious financial risk.

So, 54,000 + 1,08,000 gives you 1,62,000, 1,62,000 + 1,62,000 gives you 3,24,000 for the third year.

The cumulative downtime cost reflects the total financial impact over multiple years. For the first two years, you combine the yearly downtime costs to find the total for all operating time. Continuing this pattern allows you to see how costs pile up. For instance, after the second year, the cumulative cost is 1,62,000 rupees. If you project the same costs forward into a third year, you'll keep adding, demonstrating how the financial implications of downtime are exponential.

Imagine keeping track of your bakery's losses. In the first year, you lost 54,000 rupees, and in the second year, another 1,08,000 rupees due to increased downtime. By the end of the second year, you've accumulated a massive 1,62,000 rupees in total losses. It’s like stacking up bills – the longer you wait to fix the oven, the more the financial weight grows on your bakery's finances.

Now, you have to account for the loss in productivity. So, the loss in productivity results in increased downtime costs of the machine.

Loss in productivity occurs when machines are not functioning optimally due to downtime. This loss not only affects immediate costs but also impacts future productivity. After repairing, to match the original output rate, you may need to invest in additional operating hours, hire more workers, or even bring in extra machinery. This situation significantly inflates overall costs, making accurate cost estimation crucial.

Think of your bakery needing to run more shifts after the oven repairs to meet demand. If the oven was operational less, you'd need extra hands to make up for lost production. Just like adding staff to meet customer expectations leads to higher payroll expenses, productivity loss contributes to overall increased operational costs.

So, that results in some increase in cost due to downtime. So, that is what is called as productivity adjusted cumulative downtime costs per hour.

When calculating the productivity adjusted cumulative downtime costs, you're factoring in how much you now need to spend to return to your original productivity levels. This adjusts the cumulative cost per hour to reflect additional expenses related to repairing downtime-induced productivity losses. You're essentially adding layers to your previous calculations to ensure full transparency in expected operational costs.

If your bakery's production was reduced to 98% efficiency post-repair, it means you're working at a loss. To get back to 100%, you might have to pay extra for labor hours. Therefore, your adjusted cumulative costs reflect not just your prior losses but the ongoing costs to recover lost ground, like finding ways to speed up the baking process or hiring temporary help.

So, every year your obsolescence factor is increasing as machine is becoming more obsolete. So here we are trying to calculate the cost increased resulting from retaining the old machine with us.

Obsolescence costs arise from keeping older machines that do not match the productivity of newer machines. This cost increases over time as the machinery ages and the competition introduces better options. The longer a business retains outdated equipment, the higher the obsolescence costs due to increased maintenance and lost opportunities for higher production rates.

If your bakery holds on to an old, less efficient oven, the obsolescence costs become noticeable. As competitors release better ovens that can bake faster and at a lower power cost, sticking with your old oven means missing out on potential sales. Just as consumers choose newer, faster, and better options, businesses must consider staying updated to avoid unnecessary financial losses.

So, this is hourly basis. Now, you have to calculate for the entire year. So, yearly obsolescence costs for the second year.

Obsolescence cost per second year = 45 × 2000 = 90,000 rupees.

Once you determine the obsolescence cost per hour, you multiply it by the total operating hours to find the yearly cost. In this case, the second year's obsolescence cost amounted to 90,000 rupees. This calculation illustrates how ongoing costs can accumulate significantly when retaining equipment that depreciates in performance over time due to age.

In your bakery, if you assess the old oven’s obsolescence and find it costs you 45 rupees per hour, extending that cost across 2000 operational hours results in a hefty 90,000 rupees annual cost. Similar to a phone losing value as better models come out, your machine loses financial utility with every hour it remains in service.

So, during the 4th year it is advisable to replace your machine.

The economic life of a machine refers to the time during which the costs of ownership and operation are minimized. Analysis generally shows that while early years involve high depreciation, costs lower up to a point, increasing maintenance costs then trigger a rise in total costs. Identifying this turning point helps businesses decide when to replace machines to ensure optimal cost efficiency.

Think of a car that depreciates in value for the first few years, becoming cheaper to own. By the fourth year, however, issues like wear and tear could start to arise, pushing repair costs up. Knowing when the costs balance helps you decide whether to hold on or trade it in for a new vehicle that won’t incur those flighty repair costs.

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