Siemens
Early identification and economic assessment of process anomalies
This gives companies new opportunities for the economical optimisation of their processes. The app analyses process events that affect parameters such as productivity, availability, and quality, and alerts the plant operator to any anomalies. These events and anomalies are no longer simply identified, but also scrutinised for their business relevance—an assessment which was previously only possible based on previous experience.
Machine learning with process data
To enable the AI to detect and evaluate business-relevant anomalies, the machine-learning algorithms are trained on the basis of process data and then concentrated to determine which anomalies have an impact on the economic efficiency of the plant. The plant operators themselves then define the further focus of the AI using the app dashboard, where anomalies can be selected, evaluated and commented. This evaluation phase is accompanied by several feedback loops, so that the plant operator ends up with well-trained, focused AI that is able to evaluate anomalies, based on the process data, for their business relevance.
