Customers expect on-time deliveries, factories with good production planning run more efficiently. These are the external and internal factors that enable accurate OEE analysis and data usage. How do production planning and OEE analysis have to interact to achieve these results? We give answers.
Production planning only makes sense if it provides a minimum of precision. The APS/PPS tools available on the market all have the classic “garbage-in garbage-out” problem of information technology: They can only plan as well as they are supplied with data.
Two major and generally unused levers for increasing the planning quality are fairly consistently noticeable in factories: Incorrect expected values for the equipment occupancy time with a production order and incorrect assumptions about the set-up time between two orders. This leads to unstable planning, of which large parts have to be rescheduled in the next planning run. Not a sign of good planning. How to prevent this phenomenon?
Precise calculation of the equipment occupancy period
In order to do justice to the problems of production on the shop floor in terms of planning, the system capacity available according to the shift model is often corrected downwards by a flat-rate factor. The system is therefore no longer available with 100% capacity, but only with e.g. 78%. The value was calculated using a long-term average. If the planning performance is not achieved several times in a row, the value is corrected further downwards. This discounting is intended to account for the many minor disruptions that occur during order processing.
However, reality is more dynamic and can be mapped more precisely. The set difference is actually the OEE (minus the set-up losses). With oee.ai, this can be shown per equipment and per product and forwarded digitally and in real time to an APS/PPS system. The calculation horizon in the past can be freely selected.
In this way, you not only do justice to the product differences, but can also take improvement measures in the production process into the planning without manual parameter adjustments.
Precise planning of set-up processes
Larger planned downtimes such as maintenance or cleaning shifts are usually shown in the planning and the times are also adhered to on the shopfloor, so that they rarely lead to deviations from the plan. However, the situation is different with the set-up times. We see companies that set up their equipment pool 40,000 times a year, but plan this with a flat-rate time module of 30 minutes.
Here, too, more precision is possible through the use of oee.ai. Modern OEE systems automatically generate a setup matrix in the background, i.e. they show the duration of the setup process for all combinations from the previous product to the next product. These real durations can be assigned a statistical variance and also automatically given to the APS/PPS tool so that they can be included in the planning.
What is left of the lack of precision?
Two other factors that often cause turbulence in factory processes have not yet been addressed. Short-term and unexpected reduced employee availability due to sick leave at the beginning of the shift cannot be taken into account in planning, nor can unexpected, longer technical losses be taken into account. In terms of planning, these are individual events for which no statistical basis is readily available.
Feel free to contact us if you have any questions about the integration of PPS/APS systems and oee.ai.