Digitize production process: rapidly integrate data from enterprise systems, operational sources, sensor networks, and external providers to define the production digital twin and share it with engineers, analysts and managers.

Drive operational efficiency: improve Overall Equipment effectiveness (OEE), reducing uneven production throughput, production loss and output variability and optimizing overall yield. Detect potential anomalies or deviations earlier in the process improving first-pass yield, reducing raw material and energy usage, scrap or rework costs and unplanned downtime.

Maximize production yield of the rework process: starting from non-conformity parameters, Senseioty identifies the best rework procedure to obtain a conformance batch. This reduces non-value-added rework costs, production line usage time and raw material usage.

Information and Operational technology integration: Senseioty integrates operational data through standard protocols such as OPC UA, as well as ERP and ICT enterprise systems to create a comprehensive view of inventory, supply networks and bill of material to optimize inventory stock, supplier performances and costs.

Aggregate operational data into a federated image of multiple production sites: Senseioty analyzes data coming from multiple factories to extend and consolidate with a common data model.