OEE is an accepted key figure for high-volume processes, such as filling or packaging processes, and is also common in industries with medium batch sizes of, for example, a few dozen products. However, the development of IoT technology also makes it possible to apply OEE to very small quantities or very long-cycle processes — down to batch size 1. The key figure can provide the same advantages that have also made it attractive in the context of large lots.
OEE is made up of the factors availability, performance and quality. All three factors can also be used in lot size 1 processes, although the term “lot size 1” in this article should be understood as a simplistic synonym for very small lots and possibly long-cycle processes.
To give an idea of the concept, we are looking, for example, at a rigid-bed milling and drilling machine from the SLP series from machine manufacturer Soraluce, of which oee.ai analyses the productivity of a mechanical engineering company in Baden-Württemberg, among others.
The system is used to produce precise and long travel rails for machine tools. Cycle times are typically over one hour and the cycle consists of the steps of spanning, processing, brazing/unloading. How is the necessary process data for an OEE calculation recorded and how is OEE calculated for this application?
Calculation of the OEE availability factor for lot size 1
The determination of the availability factor and the reasons for availability problems is very similar to processes involving large quantities. A detection threshold is defined, which is usually 5 minutes for long-cycle processes. This means that if the system does not report any movement for a period of more than 5 minutes, there is a loss of availability from the start of the period — and a reason for the fault is queried on the display. This creates a background waterfall, which represents, for example, the times of opening and unplugging, technical faults or times of maintenance/TPM.
The calculation of the availability factor is therefore no different from the usual calculation as a special part of the OEE.
Calculation of the OEE power factor for batch size 1
The power factor can be identified as part of OEE calculation in two different ways, which differ significantly from classic OEE calculation. Let's take a look at the two ways:
The calculation of the power factor by comparing the planned feed with the actual feed is more common. In the program for the machine tool, the designer of the component has provided a target feed for all routes. These values are used as default speed values in this method. If the system deviates from this in real operation, this is a loss of performance. The reason for the deviation is the intervention of the plant operator, who can completely delay or even accelerate the processing process by overriding the system. If the system therefore operates at the feed rate specified in the program, a power factor of 100% is shown. In order to record the reasons for the fault, starting at an adjustable threshold value, e.g. < 80% Vorschub für > 2 minutes, the cause of the fault is queried by the operator as to why he is currently delaying the feed. This creates a background waterfall similar to that of availability losses, but with different causes.
The advantage of this calculation method is the real-time availability of the power factor, which can then be displayed on an Andon board above the system, for example. Different phases with different causes of the loss of power can also be identified for each workpiece, which means that performance recording takes place very precisely.
Another variant of identifying power losses is based on the subsequent measurement of the te. The te describes the piece time that the work preparation has calculated for the workpiece. In addition to the set-up time, this is often shown in the production order for the PPS system. In long-cycle processes, te is the time between opening and unloading, which is loss of availability according to the OEE definition. If the time difference between the end of clamping and the start of unloading exceeds te, a percentage excess of te can be calculated, which corresponds to the average loss of power during workpiece processing. If this form of loss of productivity is identified, the employee receives an input prompt at the end of processing for a fault, which in this case will usually be a collection reason for the loss of the entire workpiece, which reduces the precision of the recording compared to the first recording option presented.
Calculation of the OEE quality factor for batch size 1
The quality factor describes whether the manufactured workpiece is within or outside the specification. Therefore, if the OEE application also queries the OK or N.O.O. status together with the fault reason unloading, this information can be applied to the previous processing time of the workpiece. Here, too, a fault cause of the message, such as lack of dimensional accuracy, surface defects, etc., can of course be included.
Data collection for OEE batch size 1
When collecting data to calculate the OEE for small batches or long cycle times, the data from the machine control system must be accessed. With modern systems, such as the Soraluce SLP series shown, this data is easily available via OPC UA with an MQTT data transfer. Older systems without the technical option require a connectivity retrofit. Thanks to advances in i4.0 technologies, this too is now possible at low cost. For more information on this topic, please here.
Are you interested in recording productivity in the operation of systems with long cycle times or small batches? Feel free to talk to us. We offer test installations at a low fixed price as part of a proof-of-value project.