OEE can be improved by increasing one or more of its three components - availability, performance rate or quality rate. First, since the OEE time loss model is dependent upon an accurate equipment design speed, this rate must be set at a realistic value. If it is set too high, then the OEE will be abnormally low. Point 85 has three charts in the equipment's dashboard that are used in analyzing OEE.
The time loss categories are displayed in a summary bar chart to arrive at the Value Adding time. For example:
By hovering the mouse over a section of a horizontal bar, more information is displayed. In this chart we see that Minor Stoppages accounted for 40 minutes of lost time during the available equipment time of 200 minutes (20%).
To assist with analyzing the reported OEE, Point 85 has two Pareto chart types - first and second level. Pareto charts are useful for determining which components deserve more detailed analysis. The first level Pareto shows percentage of available time lost in a loss category. In the example below, Minor Stoppages consumed 20% of the available time whereas Unplanned Downtime was 12%.
By clicking on a bar or by selecting the corresponding tab, a second-level Pareto chart will be displayed. For example, for the 20% of the time assigned to Minor Stoppages,
40% was due to the "Jam" reason and 22% to "No Part":
Jams could be reduced by determining the root cause and fixing the problem. "No Part" could be fixed by ensuring that there is an adequate factory floor inventory of that part.
Mean Time Between Failures (MTBF) and Mean Time to Repair (MTTR) are directly related to OEE through its availability component. The larger the MTBF is, the higher the OEE will be since the available time is high.
If availability events are entered as they occur (vs. in summary form), the MTBF and MTTR will be shown in the Availability tile of the equipment's dashboard below the current loss category. MTBF (in hours) is calculated as the average time between successive unplanned downtime events. MTTR (in minutes) is calculated as the average time between the first availability event after the failure that is not unplanned.
For example, this equipment (which is now running normally) has experienced unplanned downtimes at an average of every 2.5 hours, and took an average of 43.3 minutes to fix the cause.