OEE VS Asset Utilization: What is the Difference?

Author Lewis Dixon, February 8, 2024

OEE (Overall Equipment Effectiveness) and AU (Asset Utilization) are the two most well-known and important metrics to measure a manufacturing plant’s performance.

Yet, while these two metrics, at first glance, may seem similar to each other, they aren’t one and the same, and in this guide, we will learn about their differences.

By the end of this guide about OEE vs. AU, you’d have learned about:

  • What is AU (Asset Utilization)?

  • What is OEE (Overall Equipment Effectiveness)?

  • The main differences between OEE and AU

  • How to use both OEE and AU to improve your plant’s efficiency and productivity

  • Other related metrics

And more.

 

Key takeaway:

 

At first glance—only looking at their names—AU and OEE may seem very similar to each other:

  • Asset Utilization measures how well an asset (i.e., a piece of equipment, a system, a tool, etc.) is currently utilized compared to what it could do

  • Overall Equipment Effectiveness measures how well a piece of equipment or a system (an asset) performs in achieving its manufacturing objective in its current production schedules

 

The key difference between the two, however, is how the two metrics compare equipment availability with total uptime:

  • Asset Utilization takes into account all the available time for the asset (Availability) 

  • OEE takes into account only the scheduled production uptime for the asset (Uptime)

 

For example, if a machine is scheduled for seven hours on an eight-hour shift, the Uptime is 7/8 or 87.5 %, while the Availability is 7/24 or 29.1%. At first glance, Asset Utilization leaves out important data that could be used to improve productivity, but each calculation has its advantages.

 

What is Asset Utilization?

 

Asset Utilization measures how intensively an asset (machinery, equipment, system, process, etc.) is utilized compared to what it theoretically could do. 

In manufacturing plants, the utilization of an asset will affect its life cycle.

Underutilizing an asset may result in a longer life cycle for the said asset, but obviously, it will result in lower output. Not to mention, regular maintenance costs will still apply (albeit they can be reduced.) Underutilization is generally viewed as bad and may indicate insufficient demand, inefficiencies, or excess production capacity. 

On the other hand, overutilizing an asset can increase its output, but it may result in a shorter life cycle (earlier replacement) and costly repair costs in between. While high asset utilization is generally a good thing, it shouldn’t result in neglected maintenance. On the other hand, overly low asset utilization is typically considered bad, as it may indicate insufficient demand, excess capacity, or inefficiencies/bottlenecks that reduce uptime.

Measuring Asset Utilization essentially allows the manufacturing plant to identify optimal utilization of assets to maximize its output and life cycle. 

In practice, you can measure Asset Utilization (AU) at different levels: for individual pieces of equipment, for product lines, and for the entire manufacturing plant/the whole operation.

To summarize, AU measurement can offer three main benefits:

  1. Allowing the manufacturing plant to accurately measure theoretical maximum output without bottlenecks

  2. Revealing inefficiencies and their causes; allowing the plant to drive an improvement strategy

  3. Allowing the manufacturing plant to identify the optimal fixed costs of assets. Since fixed costs are divided across the number of items produced, the lower the output, the higher the per-unit costs. 

 

How to calculate Asset Utilization

 

While there’s no accepted industry-standard formula (and definition) for asset utilization, most organizations define Asset Utilization as the ratio of actual manufacturing output to the theoretical maximum output for 365 days/year while producing 100% good/non-defective products.

 

Simple AU calculation

 

From this definition alone, we can see that we can calculate Asset Utilization with only two variables: Actual Output and Theoretical Maximum Capacity, and we can calculate AU using the following formula:

Asset Utilization = (Actual Output / Maximum Capacity) x 100

For example, if we know that the theoretical maximum capacity of a machine is 1,000 tons/day while in a day’s shift, the machine produces 980 tons (actual output), then:

Asset Utilization = (980 / 1,000) x 100 = 98%

 

Alternative method: calculate time utilization

 

If, for one reason or another, you can’t accurately determine the Actual Output (for example, if there’s an inconsistent number of defective products in each batch,) then another common approach to calculating Asset Utilization is to calculate the percentage of actual time utilized to the total number of hours available, or: 

Asset Utilization = Actual Time Utilization/ Total Number of Hours Available

However, measuring actual time utilization in a complex manufacturing process can be quite challenging, as there are various possible factors that may cause unused, wasted, or lost hours. 

To accurately measure actual time utilization, you should take into account the following factors:

 

  1. Planned downtime

 

The first thing you should do is identify the planned downtime of your manufacturing process: scheduled maintenance, changeovers, required replacements, etc. If you are planning to measure an annual Asset Utilization, then you should also calculate the annual planned downtime. If you’ve kept a comprehensive historical record of your maintenance schedules (in your maintenance management system (MMS) or manually, then this shouldn’t be a major issue. 

 

  1. Lost operations time

 

Identify the total (unplanned) lost operations time for various reasons: equipment failure, holidays, breakdown, absent operators, and so on. Very importantly, if this piece of equipment does not operate 24/7 for the whole year, any inactive hours should be calculated as lost operations time. 

 

  1. Unplanned downtime

 

Identify the total unplanned downtime during the measurement period: any unexpected equipment failure causing downtime, etc. 

 

  1. Production hours losses

 

Take into account the total number of lost production hours for one reason or another: changes in production schedules due to poor sales, bottlenecks causing production slowdowns, etc. 

Any losses should be accurately documented. For example, if your machine has a theoretical maximum capacity of 1,000 units per hour but, for one reason or another, has only been operating at 800 units, then this 20% loss should be recorded as a 20% reduction in the overall production time.

 

  1. Quality losses

 

Any time spent manufacturing defective parts/products and remaking bad products should be considered loss hours. Ideally, the number of bad units produced should be converted into the time needed to produce them and calculated as loss time. 

Once you’ve got all the figures above, simply add all of them together and then subtract this total from the total number of available hours in the measurement period.

 

Ideal AU Calculation

 

An ideal AU calculation should take into account three key variables: Availability, Performance, and Quality. This is quite similar to OEE calculation (more on this later), which often results in confusion between the two metrics.

The ideal AU formula is:

Asset Utilization = Availability x Performance x Quality

Whereas

Availability = Operating Time / Calendar Time

Asset Utilization calculation assumes that the manufacturing process runs 24/7 for 365 days (Calendar Time) 

If a manufacturing plant operates on an 8-hour shift each day, AU calculation takes into account that a day is 24 hours and ignores the fact that the process doesn’t run for 16 hours every day.

Performance = (Ideal Cycle Time x Total Production Count) / Run Time

Ideal Cycle Time is the fastest theoretical cycle time that the machine can achieve in its most ideal circumstances. Ideal Cycle Time x Total Production Count results in Net Run Time (the fastest possible time to manufacture the products/parts.)

Quality = Good Units/ Total Units

Good Units, also called “First Pass” Units are parts/products that don’t need any rework to meet the required specifications. 

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What is Overall Equipment Effectiveness (OEE)?

 

Compared to Asset Utilization calculation, OEE is a relatively more detailed method to calculate the percentage of manufacturing time that is really productive

OEE takes into account three different variables: Availability, Quality, and Performance.

A 100% OEE score means the manufacturing process is only manufacturing good/non-defective parts (100% Quality) as fast as possible (100% Performance) and without any downtime or stop time (100% Availability.) 

 

How to calculate OEE?

 

OEE can be calculated with one simple formula that is similar to the ideal AU calculation above:

OEE = Availability x  Performance x Quality

Thus, we have to first calculate the scores for Availability, Performance, and Quality.

 

Availability

 

An availability score of 100% means that the manufacturing process is always running during the scheduled manufacturing time. 

Availability takes into account two key losses: Unplanned Stops and Planned Stops, and can be calculated with the following formula:

Availability score = Run time / Total Scheduled Manufacturing Time

whereas

Run Time = Total Scheduled Manufacturing Time - (Planned Stops  + Unplanned Stops)

In an OEE calculation, Scheduled Manufacturing Time is taken into account rather than Calendar Time. Meaning if the manufacturing plant operates on an 8-hour shift each day, then only these 8 hours are taken into account in the calculation. This is the main difference between OEE and AU calculations.

 

Performance

 

A Performance score of 100% means the manufacturing process is running as fast as possible throughout the scheduled production time.

Performance takes into account two key losses: Slow Cycles (situations when the process is running slower than its Ideal Cycle Time) and Small Stops (downtimes under certain thresholds.)

Similar to the ideal AU calculation, in OEE, Performance score can be calculated with the following formula:

Performance = (Ideal Cycle Time x Total Production Count) / Run Time

 

Quality

 

A Quality score of 100% means the manufacturing process only produces good parts without any defects.

Quality takes into account defective parts, including parts that need rework, and—again similar to AU calculation— can be calculated with the following formula:

Quality = Good Units/ Total Units

 

Difference in calculating OEE and AU

In practice, only three key pieces of data are needed to calculate OEE and AU: 

  • Good Count:  the number of parts/products that are defect-free the first time they were produced. This data can be obtained manually (by placing a human counter to count good parts after the constraint) or automatically by using a sensor that is triggered only for good parts.

  • Ideal Cycle Time: is the theoretical maximum time to produce a single part or product. For an accurate AU/OEE calculation, it’s crucial that Ideal Cycle Time is an honest measure of how fast the process can run. The preferred method to capture Ideal Cycle Time data is to use Nameplate Capacity—the design capacity as specified by the equipment’s manufacturer; alternatively we can perform a manual time study to measure the absolute fastest time the equipment can produce.

  • Scheduled Production Time: as the name suggests, this is the total time that the machine is scheduled for production. Depending on your policies, certain types of planned stops may be excluded (most companies exclude breaks, including lunches.)

 

By collecting these three types of data, we can calculate OEE and AU with the following formulas`, which are the result of substituting the equations for Availability, Performance, and Quality (as discussed above) to reduce them to their simplest terms:

OEE = (Good Count x Ideal Cycle Time) / Scheduled Production Time

 AU = (Good Count x Ideal Cycle Time) / Calendar Time

Let’s use a fictional manufacturing process example to illustrate the difference between the two:

A machine is scheduled to run in an 8-hour shift, 5 days a week, and has a Nameplate Capacity to produce 1 part per minute. A sensor counts that the process produces 410 good (first-pass) parts each shift.

 

In this example: 

  • Good Count = 410 units

  • Ideal Cycle Time= 1 (minute)

  • Scheduled Production Time= 480 minutes - 60 minutes (breaks) = 420 minutes

  • Calendar Time = 1,440 minutes (24 hours)

 

With this data, the OEE and AU for the shift are:

OEE = (410 x 1) / 420 = 97.6%

AU= (410 x1) / 1,440 = 28.4%

The difference, as we can see, can be very significant. 

AU illustrates how well the machine (asset) is currently being utilized by taking into account all losses, not just those directly associated with the scheduled production process. This allows the business to plan—for example— longer shifts to maximize utilization in the future.

 

Comprehensive performance monitoring: other metrics to monitor

 

Having a clear set of meaningful manufacturing KPIs and metrics will not only help you measure your plant’s current performance but may potentially give you a glimpse into the future. You’ll get a look at what’s going to happen, so you can make the necessary adjustments to avoid potential disasters.

Throughout this guide, we’ve learned how Overall Equipment Effectiveness (OEE) and Asset Utilization (AU) are two of the most important metrics to monitor when it comes to measuring manufacturing performance. However, there are three other metrics that are worth considering in order to have a more comprehensive picture of your business’s effectiveness and productivity:

 

  1. Unplanned downtime

 

Although unplanned downtimes (stops) are often discussed when measuring OEE, unplanned downtime deserves a discussion on its own to help paint a more well-rounded picture of your manufacturing productivity. 

It’s considered good practice to take down equipment from time to time, especially for maintenance/changeovers. This is called planned downtime, and it should not significantly affect manufacturing output.

Unplanned downtime, on the other hand, happens when something unexpected stops the equipment from running: a shortage of materials, machine breakdown, component failure, etc., and they can significantly affect output.

It’s crucial to closely monitor the frequency of unplanned downtime. If there are too many unplanned stops and/or if there is an upward trend in frequency, then you should identify the underlying issues.

You can calculate unplanned downtime with the following formula:

 

Unplanned downtime = (total downtime - planned downtime) / total available time

For example, if the planned production time for the batch is 8 hours, and the planned maintenance/changeover is 1 hour while there’s an actual total downtime of 1 hours and 30 minutes, then:

 

Unplanned downtime = (1.5 - 1) / 8 = 0.0625 or 6.25%

 

  1. Product yield

 

Product yield refers to the ratio of good parts/products manufactured in a batch to the total number of planned parts/products. 

Product yield can provide you with valuable insight into which equipment is working effectively and which is producing too many defective parts/products. 

You can measure product yield after you’ve collected three variables: 

  • P for the planned number of parts

  • G for the percentage of good parts produced in the batch

  • R for the percentage of reworked bad parts that are ready for sale after rework

 

After you’ve figured out the numbers for these variables, then you can calculate product yield with the following formula:

 

Product yield = (P x G) + (P x (1 - G) x R)

 

For example, a total of 100 parts are planned for the batch, and the result of the batch is 80 good parts ready for sale. For the remainder that needed to be reworked, 60 percent will become ready for sale. 

 

Product yield = (100 x 0.8 )+ 100 x (1-0.8) x 0.6) = 80 + (100 x 0.2 x 0.6) = 92

 

This example of a fictional manufacturing process can create 92 salable products in each batch.

 

  1. Maintenance spend

 

Measuring maintenance spend would provide you with a good insight into the condition and age of each piece of equipment.

An increasing trend of maintenance spending can be a sign that your equipment needs more maintenance (and it may also result in rising unplanned stops.) This may indicate that this specific piece of equipment needs to be replaced. 

You can calculate maintenance spend with the following formula: 

 

Maintenance spend = total maintenance costs/ total cost of goods sold   

 

Monitor your OEE and Asset Utilization with LineView

 

Accurate monitoring of OEE, Asset Utilization, and other performance metrics will give you the opportunity to make sustainable improvements in your manufacturing productivity. 

Yet, compiling accurate utilization and performance data can be challenging in many manufacturing plants and organizations. Data can often be buried, and sensors can capture inconsistent values, resulting in inaccurate information that won’t bring much value to your business. 

This is where you can leverage smart factory solutions like LineView to make sure you are always getting accurate and detailed insights into how your machines and equipment performs, including accurately capturing valuable OEE and Asset Utilization data.

LineView’s approach simplifies your daily routines, gives you data to make good decisions, and provides technical expertise to solve your challenging production issues.

 

 





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