FEATURE Smart factories
Feature sponsored by
The road to data transparency By Charlie Walker, Digital Solutions Consultant for SICK UK T it?
The gritty reality of a production fl oor can be a far cry from the yellow brick road of a digital journey. If you feel daunted, that’s understandable. It’s likely you will have diff erent machines in diff erent places 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 diff erent communications protocols. Faced with a sea of information, it’s
diffi cult to isolate the specifi c factors that are limiting your operating effi ciency. 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 fi nd 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 confi gure 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 fl aws in their processes as they go. Taking and aggregating information from diff erent systems could be a slow process, undertaken only at intervals or as part of special projects. Even where there are existing data analysis systems in place, including those that operate at a higher organisational level, the opportunities to adapt them to deliver more data can be limited.
22 November 2023 | Automation
he road to digitilisation can seem littered with jargon and clichés, although the promised benefi ts of digitilisation are simple enough:
extract more data from your existing plant and equipment, analyse it to gain better insights which inform better operating decisions.
Analysing data across your production and logistics operations enables real-time monitoring of the health of machines, and predicts and avoids failures before they happen. You make timely interventions to improve overall effi ciency and operate at peak performance by minimising unexpected down time. That certainly sounds like a result, doesn’t
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 effi ciency gains? There are three common questions that operators want to fi nd out: • How are my assets performing now? • What are the bottlenecks in my process? • What more could I learn by aggregating data from diff erent systems?
Field Analytics SICK Field Analytics is a vendor-agnostic data-intelligence platform that collects and aggregates data from any source, including sensors, machine controllers and other IIoT devices. The software can be confi gured to display real-time data, to provide timely alerts and alarms and to visualise historical trends through powerful dashboard graphics.
The digitilisation 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,
SICK FTMg with monitoring box for energy monitoring
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 process anomalies that might otherwise lead to machine downtime. Field Analytics can, therefore, be used to track overall operating eff ectiveness. The dashboard features can display historical trends for measurements important to an organisation’s profi tability and effi ciency, such as compressed air usage. Organisations can confi gure their Field Analytics package to better understand the condition of their machinery using powerful dashboard graphics and visual alerts. 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 fl ow sensors, they can set up dashboards for many diff erent parameters, and quickly identify and correct energy losses in their operations. 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.
CONTACT:
SICK (UK)
www.sick.co.uk
automationmagazine.co.uk
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46
