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OEE Displays and Software for Continuous Improvement of Factory Performance


OEE displays and software measure production rate, downtime, total produced and total rejected. They give a real-time indication of your lean manufacturing production line performance to help you achieve continuous improvement in your processes.

The beauty of a real-time OEE system is that you can respond immediately to any drop in performance before it becomes critical.

OEE displays and software boost production performance

Our OEE software and display systems are available in a wide range of formats to suit your installation's maximum required viewing distance and can accept data in a type which best suits you, such as pulse counts, barcode scanner, manual input, csv, database query etc.

Below is a diagram showing the main components and stages of a simple OEE display system for factory performance monitoring...



OEE large display system



Our OEE systems are modular, so we can combine as many values on the display or in the software as you would need. For example, the simplest version could show OEE, but you could additionally show Current Rate, Average rate this shift, total downtime, Quality %, Takt time, Text messages etc.

Shown below is a typical OEE software example of an Operator's screen showing real time graph of OEE versus target, with Gantt chart of all stoppages, calls for help, engineer attendance and response times etc...

OEE Software Display operator screen

Custom OEE monitoring to optimise production line performance

How do I calculate OEE?

OEE is calculated in the display itself or in the software. If your display is a self-contained OEE version, you simply connect power and pulse inputs for total made and total rejected. You will also need to tell the display how many items your production line can produce in an hour, when operating at its peak of performance.

The pulse signals can come from NPN or PNP sensors, PLC outputs etc.

If you are using our OEE Software, the measured OEE value can be saved to a cloud-based database for viewing on your laptop, PC or phone, thanks to the latest in IoT secure technology.

Trend graphing allows you to instantly see whether performance is improving or not, and for which KPIs. The three core KPI's we look at when determining OEE are Availability, Speed Performance and Quality.

OEE = Availability x Speed x Quality

  • Availability: This is the percentage of time the production line has been operational, over the chosen analysis period.
  • Speed: This is the number of items produced, as a precentage of what the line would have produced ideally, over the chosen analysis period
  • Quality: This is the percentage of good items produced, from the total of all items produced, over the chosen analysis period


If Availability, Speed and Quality are all 100%, OEE is 100%, because 100% of 100% is 100%. I all are 50%, the OEE is 12.5% because 50% of 50% is 25%, and 50% of 25% is 12.5%

OEE can be highly sensitive to small drops in performance in each of the 3 key measurements.

For example if your Availability, Speed and Quality were all at 80%, your OEE would drop dramatically to 51%

And if your Availability, Speed and Quality were to drop to 50%, your OEE would drop even more dramatically to under 13%

So to maintain a high OEE, you must be vigilant to any small drops in all your KPIs, Availability, Speed or Quality.

OEE needs to be treated with caution though, as it is not ideal and doesn't suit all processes equally, especially if there is a large mismatch between A P and Q. Ideally A P and Q would have similar values, in a well balanced and defined production system.

OEE can provide an unfair overall picture, if one or two of the variable are consistently poor, yet the remaining perform well. The reason for this is that the availability may be perfect, but speed and quality very poor, which penalises the apparent rating for availability, and may not give enough focus on the real problem areas, when only OEE is viewed..

Similarly, a very high speed, above 100% of rated operation, can give rise to lower quality than a lower speed, due to operator errors, machine jams etc, and the overall profit could be less than for the same OEE at a lower speed.

Examples of a basic OEE software report

Basic OEE Analysis this job

=====================
Line 3
=====================
74 = job id
=====================
50025 = Job chosen
Kevin Smith = Person Responsible
130/hr = target rate
1 = items per pulse
496 = total pulses this period
0 = manual additions this period
3 = manual subtractions this period
496 = total items made this period excluding manually entered items
493 = total items made this period including manually entered items, but excluding rejects
662 = Target of how many should have been made this period
Fri 21st Jun 2019, 07:04:37 = Job chosen When
Fri 21st Jun 2019, 12:10:17 = Job completed When
2.872 = total stoppage time in hours
8 = total stoppage occurrences
5.094 hours = elapsed time this job

0.744 Performance this job
0.436 Availability this job
0.994 Quality this job

32.3% OEE this job

=====================


Basic shift summary, all jobs

9hrs = Elapsed time this whole period (including changeovers)
493 = grand total items made good
3 = Grand total Rejects
662 = Grand total target quantity
5.094hrs = Grand total elapsed job time

0.745 = performance overall
0.247 = availability overall
0.994 = quality overall

18.3% OEE Overall




We also collect the following useful information:

  • Reasons for downtime, selected from a user-defined library
  • Downtime per reason
  • Engineer's response speed to call for help
  • Engineer's time to resolve
  • Average time to resolve each downtime reason


An example of a production software screen we designed for use on an Android or iPhone device.

tablet screen for a production operator

OEE display and software system information leafletOEE Display and Software system information leaflet


OEE display for a cardboard factory

cloud based data logger and trend analysis system




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