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FEATURE SENSORS & SENSING SYSTEMS NAVIGATING A ROUTE TO
Extract more data from your existing plant and equipment. Analyse it to gain better insights. Make better operating decisions. But how do you go about this? Charlie Walker, digital solutions consultant for SICK UK, explains
T
he promised benefits of digitalisation are simple enough: Aggregating data across your
production and logistics operations enables real-time monitoring of the health of machines, predicts and avoids failures before they happen. 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? Yet the yellow-brick road to
digitalisation is littered with jargon and clichés. Worthy advice from management consultants is often accompanied by snappy graphics charting a conveniently neat, linear progression along the data transparency superhighway from zero to digital superhero.
A SEA OF INFORMATION The gritty day-to-day reality for engineers can make the digital journey feel daunting, and that’s understandable. It’s likely different machines in different places across production and logistics floors are not connected. Even if your IT systems are not operating entirely separately,
systems in place, including those that operate at a higher organisational level, the opportunities to adapt them to deliver more data can be limited. There can also be reasons the use of cloud-based systems is undesirable because of data security concerns. So, what can be done to get around these
real-world limitations? How can you circumvent the barriers and end up with a helicopter view of your operations? How do you drill down to really useful and timely information that can inform cost savings and efficiency gains?
TRACK AND TRACE EXPERIENCE SICK’s software development team set about addressing these challenges by turning to the experience of working with our customers in the logistics industries. An analytics engine had already been perfected with our global customers for almost a decade. It has helped them achieve automated and accurate data transparency to run track and trace applications within their distribution centres more efficiently and provide competitive advantages to their organisations. The result is an on-premise Field
your data could come from many sources that use different communications protocols. Faced with a sea of information, it’s difficult
SICK FTMg flow sensors can be
positioned strategically to feed back compressed air usage data
to isolate the specific factors that are limiting operating efficiency. Information could just be recorded manually, such as 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.
A 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. Even where there are existing data analysis
22 DESIGN SOLUTIONS MAY 2024
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. There are three common questions that
operators want to find out: • How are my assets performing now? • What are the bottlenecks in my process? • What more could I learn by aggregating data from different systems? SICK Field Analytics is vendor agnostic. It
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.
FIELD ANALYTICS The digitalisation 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, additional smart sensors and edge devices can be added to machinery or automated systems to extract the data needed. 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 both historically and in real time. Through real-time alerts, they can react more quickly to production or
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