Opening a window to smarter plant data

The gritty reality of a production floor can feel a far cry from the yellow brick road of a digital journey. Yet, there’s no end of advice for engineering teams to travel the Industry 4.0 “journey” and reap the promised rewards of greater added value for their businesses. If you feel somewhat daunted, that’s understandable.

© Image Copyrights Title
Font size:
Print

The promised benefits sound simple enough: extract more data from your existing plant and equipment, and evaluate it to gain better insights. These, in turn, 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 efficiency and operate at peak performance, by minimising unexpected downtime. That certainly sounds like a result, doesn’t it?

Disparate data sources
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 your 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. 


Read the full article in DPA's February issue


Previous Article Morrisons launches smart shelf labels across its stores
Next Article Weather forecasts could enhance sustainable manufacturing
Related Posts
fonts/
or