Industry 4.0 on-premise data intelligence platform


SICK has launched an Industry 4.0 on-premise data intelligence platform that empowers manufacturing and logistics organisations to optimise their operating performance. SICK Field Analytics can be quickly and easily set up to provide meaningful, application-specific condition monitoring and process insights, independently of an organisation’s existing machinery and systems.

SICK Field Analytics is a vendor-agnostic digitalisation platform that collects and aggregates data from any source, including sensors, machine controllers and other IIoT devices. The software can be configured to display real-time data, provide timely alerts and alarms, and visualise historical trends through powerful dashboard graphics.

Using the SICK Field Analytics software solution and a dedicated computer, users can aggregate data from disparate machines and automation systems or augment legacy automation systems to provide additional data insights. The solution is highly scalable, enabling users to adopt it on a project-by-project basis or at a wider organisational level.

The SICK Field Analytics software platform can be used in combination with data extracted from a wide variety of existing sources, including sensors from any vendor, PLCs, and smart IIoT edge devices such as sensor integration machines. Where necessary, SICK can work with a customer to add smart sensors and edge devices to machinery or automated systems as part of a dedicated Field Analytics project. SICK Field Analytics is compatible with most common communications protocols, including Rest API, OPC UA and MQTT.

Operators can set up and trend key performance indicators. Through real-time alerts, they can react more quickly to production or process anomalies that might otherwise lead to machine downtime.

Field Analytics can also track overall operating effectiveness and trend other measurements important to an organisation’s profitability and efficiency. For example, it could monitor compressed air usage or calculate and track the production costs of energy consumption.


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