Xentara - the fast track to OEE Monitoring
The Big Idea
OEE (Overall Equipment Effectiveness) is a way of measuring manufacturing productivity, often described as the gold standard for productivity improvement. It is expressed most simply as a percentage showing how much of the time spent on production actually results in good products. So a factory that works with no interruptions, at fastest speed, and does not produce faulty products, has an OEE rating of 100%:
- 100% Availability (no interruptions or downtime)
- 100% Performance (all processes running at the highest speed possible)
- 100% Quality (no bad parts produced)
Knowing your OEE score and the values of its elements (Availability, Performance, and Quality) makes it easier to take action against the underlying causes of lost productivity.
By monitoring your production data through Xentara, you can easily set up OEE calculations and see your OEE score in real-time!
OEE is a key measurement of TPM - Total Productive Maintenance
Pillars of TPM | Activities |
|---|---|
Focused equipment and process improvement | Measurement of equipment- or process-related losses and specific improvement activities to reduce the losses |
Autonomous maintenance | Operator involvement in regular cleaning, inspection, lubrication, and learning about equipment to maintain basic conditions and spot early signs of trouble
|
Planned maintenance | A combination of preventive, predictive, and proactive maintenance to avoid losses, and planned responses to fox breakdowns quickly |
Quality maintenance | Activities to manage product quality by maintaining optimal operating conditions |
Early equipment management | Methods to shorten the lead time for getting new equipment online and making defect-free products |
Safety | Safety training; integration of safety checks, visual controls, and mistake-proofing devices in daily work |
Equipment investment and maintenance prevention design | Purchase and design decisions informed by costs of operation and maintenance during the machine’s entire life cycle |
Training and skill building | A planned program for developing employee skills and knowledge to support TPM implementation
|
Major Losses
In an ideal world, OEE would always be at 100%, as machines and workers churn along according to schedule. Sadly, in reality this is never the case. There are always downtimes for maintenance, retooling, refilling consumables, etc. Then there are minor snags like slowdowns or minor stoppages. Last but not least, 100% quality is often a pipe dream. The first unit of a lot almost always has flaws due to material still being fed into the machine, and there’s always the possibility of error.
All these factors (and many potential others) mean you lose efficiency – which is why we define them as Major Losses. The following table lists some possible examples:
Availability: Downtime Losses | Performance: Speed Losses | Quality: Defect Losses |
|---|---|---|
Setup Time | Minor Stoppages | Startup Loss |
Failures | Reduced Operating Speed
| Scrap and Rework
|
Other Losses:
|
Data Collection
OEE is a relatively simple calculation based on complex variables. While counting good and bad products is rather trivial, correctly determining the performance of a production process is a lot more complicated, necessitating a lot of data from many different sources.
The Old Days...
Yes, in the “good old days”, all information on production, machine status, consumption etc. had to be collected by hand. On paper. And remember, after all that tedious data collection, some poor chap still had to manually do the calculations…
Today: Xentara Enabled
Now, Xentara allows you to collect data from your entire shop floor automatically and in true real-time.
With its unprecedented open I/O interface and modular Skill system, Xentara is able to connect to anything in your factory – from a single sensor to an array of PLCs. No matter whether you’re building from the ground up or digitalizing a Brownfield environment, with Xentara you can seamlessly acquire and collate data via legacy field buses or IoT protocols, directly from supported sensor hardware or all kinds of other sources. It is the “missing link” on the shop floor and the perfect bridge between OT and IT that Industry 4.0 has been waiting for.
The Xentara ecosystem is constantly growing. Most important industry buses are supported, and new connection Skills are being constantly developed at an ever increasing rate. These are just a few examples of the standards included with Xentara:
The collected data is collated and organized in Xentara’s semantic data model. Here it can be filtered and processed right inside Xentara before it is e.g. streamed to InfluxDB, where AI and Machine Learning entities automatically analyze your collected data. The results are available immediately, allowing you to see any changes “live” as they happen. You always have all production parameters as well as status information right at your fingertips.
All the complicated calculations that used to be done once per week from stacks of paper forms now run in the background and update themselves continually. OEE no longer is a weekly or monthly report, but a live impression available at any time, always up to date. And tools like Grafana make it simple to create individual dashboards for any specific values or calculations you want to see.
Due to its real-time nature and immaculate timing control, Xentara – unlike any cloud based IoT platform – can even feed back the insights from your analysis right into the currently running processes, resulting in a production that constantly optimizes itself – but that goes beyond the topic of OEE.
Appendix: FOR THE NUMBER CRUNCHER
OEE is calculated by multiplying the three OEE factors: Availability, Performance, and Quality.
Availability
Availability takes into account all events that stop planned production long enough where it makes sense to track a reason for being down (typically several minutes).
Availability is calculated as the ratio of Run Time to Planned Production Time:
Availability = Run Time / Planned Production Time
Run Time is simply Planned Production Time less Stop Time, where Stop Time is defined as all time where the manufacturing process was intended to be running but was not due to unplanned stops (e.g., breakdowns) or planned stops (e.g., changeovers).
Run Time = Planned Production Time − Stop Time
Performance
Performance takes into account anything that causes the manufacturing process to run at less than the maximum possible speed when it is running (including both slow cycles and small stops).
Performance is the ratio of Net Run Time to Run Time. It is calculated as:
Performance = (Ideal Cycle Time × Total Count) / Run Time
Ideal Cycle Time is the fastest cycle time that your process can achieve in optimal circumstances. Therefore, when it is multiplied by Total Count the result is Net Run Time (the fastest possible time to manufacture the parts).
Since rate is the reciprocal of time, Performance can also be calculated as:
Performance = (Total Count / Run Time) / Ideal Run Rate
Performance should never be greater than 100%. If it is, that usually indicates that Ideal Cycle Time is set incorrectly (it is too high).
Quality
Quality takes into account manufactured parts that do not meet quality standards, including parts that need rework. Remember, OEE Quality is similar to First Pass Yield, in that it defines good parts as parts that successfully pass through the manufacturing process the first time without needing any rework.
Quality is calculated as:
Quality = Good Count / Total Count
This is the same as taking the ratio of Fully Productive Time (only good parts manufactured as fast as possible with no stop time) to Net Run Time (all parts manufactured as fast as possible with no stop time).
OEE Formula
OEE takes into account all losses, resulting in a measure of truly productive manufacturing time. It is calculated as:
OEE = Availability × Performance × Quality
If the equations for Availability, Performance, and Quality are substituted in the above and reduced to their simplest terms, the result is:
OEE = (Good Count × Ideal Cycle Time) / Planned Production Time
This is the “simplest” OEE calculation described earlier. And, as described earlier, multiplying Good Count by Ideal Cycle Time results in Fully Productive Time (manufacturing only Good Parts, as fast as possible, with no Stop Time).
Why the Preferred OEE Calculation?
OEE scores provide a very valuable insight – an accurate picture of how effectively your manufacturing process is running. And, it makes it easy to track improvements in that process over time.
What your OEE score doesn’t provide is any insights as to the underlying causes of lost productivity. This is the role of Availability, Performance, and Quality.
In the preferred calculation you get the best of both worlds. A single number that captures how well you are doing (OEE) and three numbers that capture the fundamental nature of your losses (Availability, Performance, and Quality).
Here is an interesting example. Look at the following OEE data for two sequential weeks.
OEE Factor | Week 1 | Week 2 |
|---|---|---|
Availability | 90.0% | 95.0% |
Performance | 95.0% | 95.0% |
Quality | 99.5& | 95.0% |
Overall OEE | 85.1% | 85.7% |
OEE is improving. Great job! Or is it?
Dig a little deeper and the picture is less clear. Most companies would not want to increase Availability by 5.0% at the expense of decreasing Quality by 4.5%.
That’s why it’s always important to look at the three key values your OEE is based on. Still, it is a great long-term indicator for your production’s efficiency.
