In many manufacturing plants, OEE is often only 40–65%, much lower than the ideal level of > 80%. But where is the problem? Why do we invest in modern machinery and optimized processes but the actual performance is still not as expected? Below are the 5 most common reasons why the OEE index is lower than the business’s expectations and i-Soft also offers corresponding solutions based on actual data.
I. Downtime is not fully recorded
Many production lines only record downtime when it stops for a long time, while short stops of 1-3 minutes are missed. However, it is the small, repeated downtimes that cause a loss of 5-15% of Availability. Signs of these downtimes include:
- The machine stops intermittently but the report does not show
- Manual recording does not match the actual operation
- Not knowing which shift has the most downtime
i-Soft offers a solution:
- Automate downtime data collection, display in real time
- Record the cause of downtime right at the device
- Analyze downtime by shift/area/device
Solution: i-Soft’s i-OEE records downtime down to the second and automatically compiles reports.
II. Unstable production cycle (Performance fluctuation)
The ideal cycle may be 0.5 min/product, but in reality, there are many fluctuations: hot machines, lack of raw materials, slow operations… and the signs may be like this:
- Morning shift runs fast, evening shift runs slow
- Actual output is less than potential output
- Performance fluctuates only about 80–95%
i-Soft offers solutions:
- Monitoring each machine’s cycle in real time
- Analyzing the cause of the “slow cycle” by shift
- Standardizing operations & training based on data
i-OEE allows automatic cycle time data collection and warnings when the speed decreases.
III. High Defect Rates with Unknown Causes
Unstable production quality on the production line is a major cause of sharp OEE declines, but most factories don’t have data to separate by shift, by machine, and by worker. These problems can be:
- Increased product defects, but no clear source
- No statistics by defect line
- Manual error data entry is prone to errors
i-Soft offers solutions:
- Record defects by product, by line, by shift
- Automate statistics & quality reports
- Analyze data to find “most defective shifts”
Read more: i-OEE – Real time Overall Equipment Effectiveness Management
IV. OEE data is delayed (daily or weekly reporting)
When data is delayed by 1-2 days, any improvement decisions are delayed. This can be seen through:
- OEE is only summarized at the end of the day
- Unable to react when a shift is having problems
- Difficult to determine when the line starts to lose performance
i-Soft offers solutions:
- Switch to real-time OEE monitoring
- Display dashboards directly in the production area
- Automatic warning when performance drops
i-OEE updates data every second, supporting immediate action.
Read more: What is OEE?
V. No overall view of performance by shift/area/machine
Low OEE is not due to just one cause but is often the result of many different “blind spots”, such as: machine A has a lot of downtime, machine B has slow speed, shift 3 has high quality errors, or line 2 is less stable than line 1. Thus, without an overall dashboard, it is difficult to prioritize the right problem.
i-Soft offers a solution:
- Use a dashboard that displays the whole: Availability – Performance – Quality
- Monitor by shift: which shift is performing best/worst?
- Compare between lines and machines to identify bottlenecks
i-OEE provides an overview dashboard + drill-down by data layer.
So, we can see that low OEE is not due to machines but due to lack of accurate data. But based on the solution proposed by i-Soft above, factories can completely increase 10–20% efficiency without investing in additional machines, instead, factories only need to:
- Automatic data collection
- Eliminate manual errors
- See problems in real time
- Make decisions right in each case
i-OEE is the solution to help businesses achieve that. Please register now to see a live demo.
