OEE: One Metric That Can Spell Success or Failure for Your Company
In business terms, there may be no maintenance-related metric more important than Overall Equipment Effectiveness (OEE).
By accounting for availability, performance, and quality, OEE provides one of the quickest ways to assess the role of maintenance in the overall health of your company. Yet many companies either neglect to track it, or calculate it using incomplete/inaccurate data gathered using outdated paper records and spreadsheets.
World-class companies, by contrast, use CMMS solutions to track detailed information on their equipment and watch their OEE numbers carefully to target areas for improvement. These companies maintain upwards of 90% equipment availability, performance rates of 95% or more, and overall quality of 99% for an OEE greater than or equal to 85%.
So how do they achieve this level of excellence? First, let’s quickly review how OEE and each of its components are calculated:
Availability = Run Time/Total Time (accounts for Down Time losses)
Performance = Total Count/Target Counter (accounts for Speed losses)
Quality = Good Count/Total Count (accounts for Quality losses)
OEE = Availability x Performance x Quality
In order to put these calculations to proper use, world-class companies will define several specific timespans (work shifts, for instance) and calculate these OEE measures for each in order to compare them. In this week’s blog, we’ll focus on availability to see how you can drill into this metric and improve it.
Availability is the foundation of all OEE calculations because it is a straightforward measure of downtime. When it comes to improving OEE, availability is therefore the best place to start.
There are two key factors involved in availability: machine breakdowns and machine adjustments/setups.
CMMS solutions make it easy to track machine runtime in the form of logs that can be entered via smartphone, tablet, or PC. In ManagerPlus, the “Work Order Down Time” report shows the amount of time that a piece of equipment was inoperative.
In this example, we see that this forklift has been down for 65 days. Let’s assume for this example that the total number of days that this forklift should have been available is 365. The runtime would therefore be 65 – 365 or 300 days.
Thus, for this example:
Availability = 300/365 or 82%
We’re not too far off of the world-class benchmark range of 90%–so how do we get there?
First, we want to look at the asset history for this forklift in our CMMS system. If the majority of the work orders associated with it were for “Reactive” or “Emergency” repairs, scheduling more preventive maintenance will likely help reduce downtime and push us closer to the 90% range.
The Work Order History view in ManagerPlus, click to enlarge. Image has been cropped to show detail.
In this example, we see that there have been three work orders associated with reactive repairs that have been performed on this forklift—these account for the 65 days that the forklift was inoperative.
Looking more closely at each of these work orders, we see that the engine has persistent issues. In particular, we should focus on the parts, services, and notes contained on the work orders to identify common issues.
Based on this information, we can then build preventive maintenance schedules in the system to prevent full-down breakdowns in the future. Let’s say that we create a preventive maintenance schedule with some routine engine checks and part replacements—performing these tasks will require far less than 65 days, and will therefore help boost availability for this asset. In addition, CMMS solutions like ManagerPlus make it easy to create these PM tasks that can be applied to multiple assets, so in this case, a schedule single schedule could be created for all similar forklifts.
Going back to the two key components of availability: machine breakdowns and machine adjustments/setups. What we’re accomplishing by moving to more preventive maintenance is reducing breakdowns and spending a bit more time making smaller adjustments.
The key is to dive into your data and do a little research. It won’t be long before you spot patterns that can be addressed with optimized preventive maintenance schedules.
Be sure to check back in the coming weeks as we dive into the performance and quality metrics.