Data is flowing from bottom to top, firstly collected at the shop floor, and then aggregated in the CPS-izers Layer shown in light green. To achieve the decoupling of the upper two layers we use industry standard MQTT brokers for a flexible publish/subscribe mechanism. This allows each component to decide for itself what data they need for their task.
The central component in the DSC Layer, the layer that uses the aggregated data from the shop floor and connects it with other relevant production parameters, e.g. from MES or SCADA systems, is the real-time processing engine Apama. It is a commercial product from Software AG and was first used in fraud detection scenarios in the banking and telecommunication sectors. However, real-time detection of anomalies becomes more and more important for industrial production processes as well to save time and money. For our use cases the Community Edition, see https://apamacommunity.com, is sufficient and freely usable.
The general usage patterns of Apama are given in the figure below which are:
- Analyze your business data in real time
- Enrich your analytics with historical data
- Visualize your real-time and historical data in business dashboards
- Trigger actions through detection of pre-defined conditions