OEE (Overall equipment effectiveness) is a key figure in production and is used as a measure of the value added by a plant. This key figure is an indication of the effective use of the equipment, taking into account its availability, its performance and the quality achieved. OEE can be used to determine and, if necessary, improve the productivity of a plant (machines, production cells, assembly lines, etc.) as well as its losses, profitability and overall effectiveness. The software listed in this SoftGuide section on the subject of OEE provides support in the ongoing measurement of plant productivity, helps to identify the causes of faults and losses, and implements targeted measures for optimization. The software usually offers analyses of MTBF, MTTR and MTBM and provides OEE calculations.
OEE, or Overall Equipment Effectiveness, is a performance metric and is calculated as the product of three factors: the availability factor, the performance factor, and the quality factor. Calculating OEE is particularly relevant in predominantly machine-driven production environments. OEE is expressed as a percentage. The higher this percentage, the more effective the production process. The aim of determining OEE is to achieve zero-defect manufacturing and to identify and eliminate the causes of losses. The OEE value should not be used to compare percentages between two production sites, because 80% at one site may be just as good as 90% at another site. The value must therefore be tailored individually to a company or a specific site. In general, however, a value below 65% is considered a clear warning signal for the production facility. It is often useful to combine OEE results with an Ishikawa diagram.
MTBF is the average operating time between two failures and is a measure of the reliability of plants, devices, or assemblies. MTTR is the average repair time after a system failure. MTTF is the average service life or the average operating time until failure. FIT refers to failures over time, with the failure rate measured as failures per 109 hours.
An Andon board or Andon display is a visual indicator that shows the current status of production or the production line. If a disruption occurs, it can usually be transmitted directly to the Andon board. This way, the current status is visible at all times to all employees as well as supervisors.
An Ishikawa diagram is a cause-and-effect diagram or a problem-solving method used to identify possible causes of a problem. In the Ishikawa diagram, which is also referred to as a fishbone diagram, ideas about causes are collected and the relationships between the individual causes are illustrated.
TEEP stands for Total Effective Equipment Performance. This key figure is a measure of production capacity. It is calculated as a factor based on total available time and overall equipment effectiveness.
Modern OEE software goes far beyond the traditional calculation of overall equipment effectiveness. It integrates real-time monitoring, root cause analysis, and recommended actions that help companies proactively minimize downtime and sustainably increase productivity. In Industry 4.0 in particular, functions such as predictive analytics and AI-supported optimization are becoming increasingly important.
Real-time data is the key to operational excellence. OEE software with live dashboards displays availability, performance, and quality in real time so that shift supervisors can respond immediately to deviations. According to studies, such systems can increase equipment effectiveness by up to 20%, as downtime is minimized and bottlenecks are made visible.
Isolated OEE solutions are no longer considered modern. Today’s software solutions generally integrate seamlessly with ERP, MES, and CMMS systems in order to create a holistic process chain. As a result, order, production, and maintenance data are brought together in real time, enabling precise planning.
Integration with ERP systems such as SAP or Microsoft Dynamics synchronizes production plans with OEE data. MES connections extend this with detailed production control. Experts estimate that integrated systems improve planning accuracy by 15–25%.
OEE software with CMMS integration identifies recurring causes of downtime and automatically triggers maintenance work orders. This reduces unplanned outages by up to 30%, as case studies from leading manufacturers show.
OEE is more than a metric – it is a control instrument. Modern solutions provide not only figures, but also specific recommendations for action and workflows for continuous improvement (Kaizen).
Automated recording of failure reasons via button, barcode, or AI classification enables precise root cause analysis. Companies use this to systematically eliminate recurring problems – with measurable effects on the OEE rate.
Quality data such as scrap rates and rework are incorporated directly into the OEE calculation. Some systems warn of declining quality and correlate it with machine parameters to enable preventive measures.