Measuring Inefficiency: How to Calculate Equipment Downtime

Managing and reducing downtime is crucial for efficient production, especially given that unplanned downtime now costs Fortune Global 500 companies 11% of their yearly turnover, which is almost $1.5 trillion. This is up from $864 billion (8% of turnover) two years ago.

In this post, we will discuss three different methods to calculate equipment downtime in manufacturing, look at the importance of data accuracy, and the cost of downtime for manufacturers.

Equipment Downtime Calculation and Formulas

There are multiple ways to calculate equipment downtime, but we’ll focus on the two simplest methods: tallying the duration of all production stops and deducing downtime from scheduled production time and actual run time.

#1 The Stopwatch Approach: Adding Up Production Stops

Imagine production as a series of shifts. To calculate downtime for a single shift, you need first to establish the start and end times. For instance, if a shift runs from 8:00 to 17:00, the total planned production time is 9 hours.

Next, note the start and end times for each production stoppage, and calculate the duration. Repeat this for every stoppage during the shift. The sum of these durations gives you the total downtime for that shift.

To express downtime as a percentage of the shift, just do (Total Downtime / Planned Production Time) * 100%.

For instance, if you measured downtime over a week (168 hours), and your equipment was down for 20 hours, your downtime percentage would be 11.9%.

#2 The Deduction Method: Planned Production & Run Time

When you know both the planned production time and run time, calculating downtime is as simple as subtracting the run time from the planned production time. Run time refers to the actual time the production process was operating, while planned production time is the total scheduled time for production.

The difference between these two times gives you the total downtime, representing when production was scheduled but was not happening.

To express this downtime as a percentage, use the formula from the previous section.

The Overlooked Factor: The Role of Planned Downtime

In evaluating the full impact of downtime, it’s crucial to distinguish between planned and unplanned downtime. Our data suggest that manufacturers have a lot of planned downtime compared to all downtime, which is often overlooked in their calculations.

This oversight means that stops such as changeovers, breaks, planned maintenance, and cleaning are excluded from downtime calculations and accepted as inevitable losses. However, recognizing and accounting for these planned downtimes can provide a more accurate picture of overall efficiency and areas for improvement.

This is illustrated even further by the fact that shutdowns, scheduled or not, can consume up to 1%-10% of available production time.

#3 The Full Picture: Calculating Downtime by Considering All Optimizable Stops

If a manufacturer wants to consider all production stops that can be optimized, including planned ones, they would need to keep track of all instances where production is stopped. This includes not just unplanned downtime (due to breakdowns, malfunctions, etc.), but also time lost to potentially optimizable planned stops (like changeovers, planned maintenance, etc.).

The formula would therefore involve summing up all instances of stoppage time, both planned and unplanned, that could potentially be optimized:

For example, let’s say a production line is designed to produce 500 units per hour when it’s running at full capacity. Over a week (168 hours), the theoretical maximum is 84,000 units, considering that the line is running 24/7.

If the equipment was down for 20 hours during that week, and we only counted unplanned downtime, then the lost production due to downtime would be 10,000 units.

Let’s consider that another 20 hours were lost during that week to planned downtime (deemed optimizable). Then our total lost production due to downtime would be 20,000 units. This means that we’d be trying to improve our productivity and produce 20,000 units more, not just 10,000. That’s a big difference.

The Key: Data Accuracy in Downtime Calculation

Knowing the formula is only the first step in the process. Ensuring data accuracy that goes into the formula is even more important. Suppose there are no processes in place or unreliable systems (e.g., pen and paper) to capture the data that underpins downtime calculation. In that case, it can distort the actual picture and lead to poor decision-making, inefficient resource allocation, and missed improvement opportunities.

In addition, data accuracy is crucial for trust within the organization. Employees, managers, and stakeholders need to trust the data they’re using to make informed decisions. If data is consistently inaccurate, it can lead to skepticism about the data and its metrics, reducing their validity.

Therefore, it’s crucial to establish reliable data collection and verification processes to ensure the accuracy of the downtime calculations. This might involve a downtime tracking system that automates the whole process.

Remember, understanding the reasons for downtime is as important as knowing its duration. This allows you to identify patterns and determine the root causes of equipment failures or stoppages.

The Cost of Downtime and Why You Need To Master It

The cost of downtime is a significant factor in understanding the true impact of equipment failures. It includes not only the lost production but also the direct costs associated with the downtime.

• Lost revenue: This is the revenue that would have been earned from the products that were not produced due to downtime.
• Increased labor costs: If downtime leads to workers being idle or having to work overtime once the equipment is operational again, these additional labor costs should be factored into the cost of downtime.
• Repair and replacement costs: If equipment needs to be repaired or replaced, these costs should also be included in the downtime cost.

As an illustration, let’s consider the automotive sector, where plants lost 29 production hours a month, on average, at the cost of $1.3 million per hour. Moreover, unplanned downtime now costs Fortune Global 500 companies 11% of their yearly turnover, which is almost $1.5 trillion. This is up from $864 billion (8% of turnover) two years ago.

This high cost emphasizes the significance of accurately calculating and managing downtime.

Final Thoughts

Downtime calculations are essential for production management. However, it’s just as important to track and analyze the causes of downtime to prevent future occurrences. Accurate data collection is the cornerstone of downtime calculations, so ensure your data collection methods are robust and reliable.

Implementing these methods can help you reduce downtime, increase production efficiency, and, ultimately, improve your bottom line.