Digital platform "ida - intelligent data analytics" creates transparency

The technical complexity of modern production plants is constantly increasing. Sustainably ensuring machine availability requires continuous analysis of operating data to monitor production processes and identify optimization potential. The continuous analysis and processing of operating data and relevant key figures creates transparency and sustainably increases plant availability. With "ida - intelligent data analytics", Kraft has developed a solution for monitoring modern production.

Ida is a platform for and with digital services that makes it possible to manage the plant fleet as well as relevant plant information and sustainably increase the availability of technically complex plants. To achieve this, the services offered focus on the two pillars "help for self-help" and "operational data monitoring". Data sovereignty lies entirely with the operator of the platform. The platform is independent of cloud services and thus both cloud and on-premise capable.

The "help for self-help" pillar includes any digital services that enable knowledge to be digitized and made available digitally. Rapid access to relevant information means that operators can be trained more quickly on the technically complex system and faults can be rectified more efficiently. This makes it possible to achieve safer handling of the system and, at the same time, the knowledge database for a plant can grow successively over its life cycle. The rapid availability of information and the successively growing knowledge database make it possible to call up measures in a targeted manner and apply them efficiently, thereby increasing plant availability.

The "operating data monitoring" pillar comprises digital services that persist, process and prepare operating data from plants.

The "message.monitor" collects plant messages and a) visually processes them and b) analyzes them in terms of frequency, average duration and total duration at selectable time intervals. At the same time, analyses of the top messages, the hourly frequency distribution and the development of frequency and average duration of a message are provided. This makes it possible to identify and localize (emerging) sources of faults in technically complex systems and thus also to derive appropriate measures for increasing and/or securing availability.

The "performance.monitor" collects operating data and processes it. The operating data is processed into common production performance indicators, which are a) visualized in a dashboard based on shifts and b) the data can be graphically processed and analyzed in freely selectable time periods. The preparation can be done per plant element or for a cluster of elements and includes an evaluation and display of the states of the elements, the production performance broken down by product type including the average processing time, cycle time and editable events.