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Home>IIot & Smart Technology>Industry 4.0>The road to data transparency

The road to data transparency

15 August 2023

While Industry 4.0 promises a myriad of benefits, getting a system up and working in reality can be a daunting task. Charlie Walker offers advice on how to avoid being overwhelmed

THERE'S NO end of advice for engineering teams to travel the Industry 4.0 'journey'. The promised benefits sound simple enough: extract more data from your existing plant and equipment, analyse it to gain better insights which, in turn, inform better operating decisions. You make timely interventions to improve overall efficiency and operate at peak performance by minimising unexpected down time. That certainly sounds like a result, doesn’t it?

Gritty reality

Except, the gritty reality of a production floor is a far cry from the yellow brick road of digitiisation. If you feel daunted, that’s understandable. It’s likely you will have different machines in different places across production and logistics floors that are not connected. Even if your IT systems are not operating entirely separately, your data could come from all sorts of sources that use different communications protocols.

Faced with a sea of information, it’s difficult to isolate the specific factors that are limiting operating efficiency. Information could just be recorded manually, e.g. on a production targets whiteboard, be stuck in silos, or just get bogged down in bottlenecks.

Operators can also 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.

Granular approach

Pragmatically, production and logistics teams are, therefore, much more likely to adopt a granular approach to diagnosing and correcting flaws in their processes as they go. Taking and aggregating information from different systems could be a slow process undertaken only at intervals, or as part of special projects.

To address these challenges, SICK developed an on-premise Field Analytics data intelligence software platform, which 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.

Vendor agnostic and compatible with most common communications protocols, the digitilisation platform collects and aggregates data from any source. It 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, additional smart sensors and edge devices can be added to machinery or automated systems.

Powerful dashboards and alerts

Organisations can configure their Field Analytics package to better understand the condition of their machinery. 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.

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.

Early users of the system have reported learning surprising new insights, especially when they compare data from different sources for the first time. Or, by inputting a formula for multiplying a consumption measurement by a unit price, e.g. for electricity, operators can get a real-time picture of their operating costs.

For example, SICK customers around the world are now using the system to monitor their compressed air usage to calculate energy consumption. Based on data from SICK FTMg flow sensors, they can set up dashboards for many different parameters and quickly identify and correct energy losses in their operations.  

So, there is no need to be overwhelmed. Sensors and other devices provide diagnostic information and measurements, right from the heart of machinery.  Armed with quality data, useful comparisons and historical trends, you can dispense with the Industry 4.0 theory book, and instead deliver data-driven, ground-up operating improvements.

Charlie Walker is digital solutions consultant for SICK UK