Predictive Maintenance is about predicting failures in machinery, assets or equipment so that you can fix them before they breakdown.
‘Thank you, Captain Obvious!’ we hear you say.
Ok, what Predictive Maintenance is really about is optimising the way that you run your business by maintaining and running the things that it needs to operate better, whether that’s a truck, a bearing within your production line, a HVAC system… anything and everything. Bottom-line: it’s about giving your business a competitive edge.
Different maintenance approaches
In an industrial setting, there are 4 main methods taken when it comes to approaching maintenance:
- Reactive maintenance – you wake until an asset breaks or fails before fixing it
- Preventative maintenance – you schedule routine maintenance of your assets at a fixed schedule, e.g. check a water pump twice a year
- Condition-based maintenance – you maintain your assets based on basic rules from it, e.g. a truck service every 10,000km
- Predictive maintenance – you use data coming from machines or sensors, coupled with other other related data (e.g. output, temperature, energy efficiency etc.) to predict failures, scheduling maintenance at the most opportune time and only when required.
(You can read more about the different maintenance approaches in our blog: What’s the difference between reactive, preventative, condition-based and Predictive Maintenance?)
As you can see from the above, Predictive Maintenance is about efficiency and improving performance. By predicting failures of your business-critical assets or the point at which reduced performance outweighs the losses incurred fixing it, you can better manage your assets, prevent disruption to your operations, schedule maintenance more effectively and maintain peak performance (read on for more benefits!).
How does Predictive Maintenance work?
Through data analysis or, more specifically, real-time and historical data fed into an IoT platform, coupled with carefully constructed algorithms built using Data Science and Machine Learning.
In order to be able to collect and do something with this data, you will need five things:
- Sensors, meters and hardware
- Communications and connectivity
- IoT Platform
- Data Science
- Machine Learning.
If the above looks familiar, it’s because these are the constituent parts of an IoT solution. Yes, Predictive Maintenance is all about IoT.
IoT’s role in Predictive Maintenance
By utilising IoT sensors, ‘smart’ or connected devices and machinery, and integrating existing systems that are monitoring output or performance all into a single IoT platform, you’re able to collect data on how machinery is performing in real-time.
Once established, you can then utilise Data Science and Machine Learning to structure and contextualise the data, which over time enables you to spot trends in things such as performance, energy usage, increased vibrations, raised temperature, or anything else that could indicate an issue. It’s also critical to note that, for true Predictive Maintenance, you need to be monitoring many things that go into keeping a machine running: if you’re only measuring temperature readings, you might be missing the excessive vibrations that are occurring, or the fact that output is down, or that it’s drawing more energy than usual – you need to measure multiple variables to get a truly accurate Predictive Maintenance system.
Beyond this and over time, you will be able to find new trends and analyse the data to pick-up on new warning signs that mightn’t have been noticed, which means that you improve your regimen and get better at predicting when something is going to fail: the more data, the better the results.
The benefits of Predictive Maintenance
Knowing what needs fixing and when has numerous benefits:
- Reduces maintenance costs – you fix only what’s necessary and utilise your maintenance teams more effectively
- Increases asset lifespan – by getting a better understanding of your machinery and being proactive in fixes, you reduce the risk of catastrophic failures and increase asset lifespan
- Speed-up fix times – because you know what’s going wrong, your maintenance crews don’t have to look around for the answer and can get straight to the fix
- Maximises runtime – because repairs are carried out only just before failure, rather than at arbitrary time periods, you increase machine uptime
- Better scheduling – maintenance efforts can be orchestrated to occur at scheduled downtimes or switchovers, you can plan for maintenance in advance and at convenient times/when human assets are available
- You don’t carry huge stock of spare parts – you only buy what you need, when you need it
- Better purchasing decisions – a by-product of collecting data on machinery is that you can better assess individual, brand or class of asset’s performance, directing future purchasing decisions
- More accurate metrics – your IoT platform will enable you to accurately calculate the cost-of-running and ROI of assets
- Optimise operations through modelling – a good IoT platform will enable you to simulate what the effect of making changes to your operations would be before you deploy them in the field
- Greater worker productivity – by reducing machine failures, there’s less downtime and you don’t disrupt maintenance crews with unnecessary maintenance
- Improve product design – through getting an understanding of common points of failure in your machinery you’re able to direct product design improvements
- Improve worker safety – catastrophic failures can be hazardous. By preventing them, you’re creating a safer work environment for your employees.
- Improves customer experience – if your business works with a ‘just-in-time’ model, machine failures can directly impact customers, so Predictive Maintenance can help ensure a brilliant customer experience
Regardless of your business’ objectives, assets it has or the industry that you operate in, implementing IoT technology and a Predictive Maintenance solution will improve efficiency, productivity, and ultimately improve your bottom line – it turns the way you maintain your machinery into a competitive advantage.
Rayven has experience building Predictive Maintenance IoT solutions with organisations in manufacturing, facility & asset management, trucking & logistics, agriculture, energy & utilities, and infrastructure & construction – implementing them both quickly and affordably.
Speak to us today to find out more.