Splunk’s white paper on Predictive Maintenance and the future of industrial operations has some interesting thoughts on where the sector is heading.
Here at Converging Data, we help businesses make data-informed decisions to get ahead of their competition. We know from experience that data analytics can transform organisations, but this paper explains why a data-driven strategy isn’t a nice-to-have but a must-have for any business. We’ve pulled out some key points on why the future of industrial operations must be data-led.
We’re in the middle of an industrial revolution
The Internet of Things (IoT), Cloud, Big Data and Analytics, Advanced Analytics, Machine Learning, Artificial Intelligence and Augmented Reality all provide huge potential for new maintenance strategies. Companies that don’t use these methods to get ahead will soon lose out.
Preventive Versus Predictive Maintenance
Preventative maintenance is planned in advance and assumes average wear and tear. Predictive maintenance takes far more factors into account, so you’re more likely to sort out problems before they happen or avoid repairing items unnecessarily.
It can be tough to implement Predictive Maintenance
This is why:
There’s a lot of it, it’s varied, and it’s often organised into silos.
Experts are needed
Managing industrial operations is a highly skilled job. Real-world knowledge needs to be applied to data for predictive maintenance to work.
With so many data sources and no central overview, it can be hard to spot the impact of one action on everything else.
When changing IT systems can pose a risk to day-to-day operations, it can feel like there’s never a good time to do it.
But the payoff is worth it
Forward-thinking organisations are using these technologies to transform industrial operations:
- The Internet of Things (IoT)
- Cloud Computing
- Big Data
- Machine Learning and Advance Analytics
- Augmented Reality
All of these methods are working towards the same goal: bringing together all the information you have on assets in one place. Once you have visibility of it, you can start using it to:
- Identify and fix problems faster
- Get proactive about maintenance
- Link up past data with real-time signals and sensors
- Predict failures
- Forecast future performance.
Real life example: Recursion Pharma
Pharmaceutical company Recursion used Splunk (Converging Data’s software of choice) to bring together data about their lab equipment. By putting the data in one place, they can monitor and diagnose equipment issues in real time, and catch anomalies in automated operations before they make impact. This means they’ve reduced equipment downtime, improving productivity.
The future of industrial operations lies in data
To conclude, although it’s a challenge to make predictive maintenance a reality, the return on investment and the competitive advantages it brings makes it more than worthwhile. Any industry, be it Manufacturing, Energy and Utilities, Transportation and Healthcare, should take advantage of their data. Speak to us now to start your data journey.