KPI: OEE
OEE – overall equipment efficiency
OEE measures how efficiently you use your equipment.
This is the most important production KPI to understand how effectively the factory runs.
The OEE is calculated like this:
OEE = Availability X Performance X Quality
Availability* = The actual working time (of the equipment) / Available time
Performance** = The actual output per time / The standard output per time
Quality = The good products output / Total output (Good and bad)
*Available time is a tricky definition. We can take the available time the factory is running or the available time the tool is available for production (After removing preventive maintenance, “No demand”, etc). We will use all available time (no reduction) to indicate the use of the tool for higher management and use the reduced available time when we want to measure the effectiveness of the tool’s owner. In each case we will not take scheduled stops (such as holidays, weekends, etc.) into consideration.
**In the performance output we will use the Total output (good and bad) per time, not the good products per time.
***OEE is always measured on a specific time frame
1. OEE – current month
Short description: OEE per tool
Who uses it (importance): higher management (High), factory management (High), unit management (High)
Description:OEE by tool is the best indicator for the way the tool worked in the specific time frame. At a glance at the graph we can tell which tools worked the way we wanted and which had problems. When we identify the problematic tools, we can drill down to the cause. Is it the availability, the performance, or the quality?
If we go deeper, we can use the following KPI that gives us all the information in one graph:
In the graph above we can easily see that tool 35 has the best OEE. The reason is high quality and high performance. If we want to improve the OEE, we will start with the availability. If we look at tool 19 on the right, we can see that the main reason it got such a low value is the availability factor.
We get very useful information from just one graph.
2. OEE by tool by month
Short description: monthly OEE for a specific tool.
Who uses it (importance): higher management (Med), factory management (High), unit management (High)
Description: By comparing the OEE on one tool on a monthly basis we can determine if we are getting better or not. By looking at the different components we can understand the trend of the components. The following example takes tool 17 and lets us see how the OEE and the OEE components are changing in time. In the following example we can see that the main problem of the tool is the availability of the tool and on the last month the problem was the performance. Performance is the hardest component to measure. The standard should usually be the maximum output per hour per product per tool. But sometimes we have problems with reporting or for some reason we get a much higher value in the performance. Then we might get OEE over 100% like we have in January. We then either fix the data or change the standard, or understand that it is a one-time performance.
3. Average monthly OEE per factory
Short description: the average OEE of all tools per month.
Who uses it (importance): higher management (med), factory management (med), unit management (med)
Description: This KPI is used to see trends in the factory OEE. The average OEE of all tools lets us see the factory performance on a time line. This KPI lets us see the bigger picture whether we are getting better across the board or not. We can also look at a specific element in the OEE to see if we are getting better at the quality, performance, or the availability.
The graph above lets us see the trend of the average OEE. We can see that it is not going in the right direction. The graph below gets more detailed about why the OEE is dropping.
We can see that the OEE is dropping due to drop in availability and deeper drop in performance. This is very valuable information if we are looking for ways to improve.
4. 100% tool time
Short description: what the tools did during a time period
Who uses it (importance): higher management (med), factory management (high), unit management (high)
Description: This KPI gives an instant view of what the tools did in a full time period. The period of time can be a day if used on a daily basis, or a month to review what the tools did monthly. We can also use longer periods as quarters or a year to look for constant problems.
At the first glance at the graph we can see how much time we used the tools for every category.
Production (blue) – actual time the tool produced out of the period of time we chose.
Scheduled stops (red) – the amount of time we did not use the tool (weekends, holidays, nothing to produce) out of the overall time.
Setup (grey) – the setup time is usually a very important consumed time, which is why it gets a separate category. If the tools are similar, we spot the better tool owner and apply his/her methods to the other tools. Setup time reduction is usually the best and in most cases the easiest way to increase time production.
Maintanance (orange) – the time the tool is not working due to malfunction or preventive maintenance.
Production (Dark blue) – the time the tool is not working due to a problem regarding the production department, for example, no operator, misuse of the tools, lack of synchronization between tool and human resources.
Supply chain (green) – the time the tool did not work due to lack of raw or packing materials.
Technology (Black) – the output materials did not meet the spec and the parameters need to be adjusted. We measure this time since it can be reduced by using RFT methods (Right First Time) and SPC.
QA (Brown) – the time we wait for lab test or other specs test and the tool is not working (on process spec check that doesn’t stop the tool is not used here, only the time used to stop the tool is considered).
Other – all the stop time that cannot be categorized.
By looking at just one tool over a long period of time we can see what the tool is doing on average:
