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, to provide timely alerts and alarms, and to visualise historical trends through powerful dashboard graphics.
Data Insights for Improved Performance
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.
Charlie Walker, SICK UK’s Digital Solutions Consultant, says the SICK Field Analytics platform can support users to progress towards greater Industry 4.0 digital maturity:
“Operators who want to gain more insights across a production floor, factory or warehouse may feel quite daunted by the prospect of collecting and comparing data from many different machines or applications.
“Faced with a sea of information, it can be difficult to isolate the specific factors that are affecting operating efficiency. The data could come from all sorts of sources that use different communications protocols. Information could even still be recorded manually, be stuck in silos, or bogged down in bottlenecks.
“Even if operators already extract some data from their existing automation, they can find themselves locked out of PLCs or other systems, such as “legal for trade”. So, they cannot increase the amount of diagnostic data from their legacy systems, even when they replace switched devices with IO-Link sensors, or configure edge integrations using IO-Link Masters.”
Interrogate Operating Efficiency
“Field Analytics can solve these problems easily by collecting data from all these disparate sources without costly and time-consuming adaptation of existing systems. Operators can extract more information about the health of their machines, while interrogating their operating efficiency in new, and sometimes surprising, ways.”
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.
Powerful Dashboards and Alerts
SICK Field Analytics incorporates a user management module to manage access rights. The data collected will depend on each organisation, but could range from the service status of sensors through to key data about the health of machinery, such as vibration, temperature, or shock. Organisations can configure their Field Analytics package to better understand the condition of their machinery using powerful dashboard graphics and visual alerts.
Operators can set up and trend Key Performance Indicators both historically and in real time. Through real-time alerts, they can react more quickly to production or process anomalies that might otherwise lead to machine downtime.
Field Analytics can track overall operating effectiveness. The dashboard features can be also trend other measurements important to an organisation’s profitability and efficiency. For example, it could monitor compressed air usage or calculate and track production costs, for example of energy consumption.
SICK Field Analytics can also enhance the data already available from legacy automated systems, including those that operate at a higher organisational level. SICK Field Analytics is compatible with most common communications protocols, including Rest API, OPC UA and MQTT.
