Of the Earth’s 8bn population, 5bn use the web. That’s a lot of nodes, on a lot of networks. But the internet’s human user base is dwarfed by its non-human users.
Over 15 billion devices are connected on the Internet of Things, IoT, with connectivity a basic part of how they function. That number is set to double by 2030. And most of them don’t look like a laptop or server. The motion sensor that switches on your office lighting, the temperature gauge that keeps greenhouse conditions ripe for agriculture, the badge that lets you tap in and out of a building – huge numbers of these are connected to backend services like data centres and cloud applications, forming a web of machines around the world far larger that our one of people.
This IoT matters a lot to us at Strypes. Because our business succeeds by keeping your business performing – and the IoT delivers the data we need to do it. Timely software updates, 24/7 availability, five-nines uptime: all rely on real-time data, analysed intelligently and used to make informed decisions that stop problems before they start. That’s why the IoT – and the always-on remote monitoring it enables – is a huge factor in our predictive maintenance (PdM) approach.
Because when you have up-to-the-moment data about how your equipment is functioning, it’s possible to see patterns that report when a problem’s ahead, long before that problem occurs. Expected operational lifespans, precise time-before-failure, reliability for different use cases – all these rely on real-time data, not a manufacturer’s estimate. And predictive maintenance makes use of it all.
In this article, you’ll learn how IoT is best used in predictive maintenance scenarios, with the business drivers for each and the different platforms that support it. You’ll also see how the hardware of sensors and connections works with the software of data analytics, and how both are needed for the most cost-effective maintenance strategy.
Let’s get started!
PdM versus other approaches: defining IoT remote monitoring
If you’ve read our other articles, you know what PdM is. So instead let’s summarise what it isn’t.
PdM isn’t “reactive”. It’s not about fixing things as they arise, basically waiting for trouble to happen – in fact, it’s the precise opposite. Nor is it “preventive”. While Preventive Maintenance (PvM) shares some traits with PdM, PvM can be wasteful: it’s an approach of retiring or refurbishing equipment early, before it reaches its maximum lifespan. Which can mean getting rid of perfectly functional infrastructure too early. (And servers aren’t cheap.)
So you could say IoT remote monitoring defines predictive maintenance. Because it’s that web of sensors – timers, thermometers, scopes, infrared cameras, motion detectors – that provide the data for PdM to work its magic.
A server in a cool, air-conditioned room may have a useful life of eight years plus. But that same machine in an overheated cupboard will suffer higher temperatures, dustier air, perhaps knocks and shakes from nearby workers. Its lifespan will be shorter. Wait for problems, as with reactive maintenance, and your IT team will be regular visitors to the dusty cupboard. Err on the side of caution – with preventive – and you’ll be throwing a perfectly good machine on the scrapheap.
The goal is to get the most useful functionality from every device … depending on its individual circumstances. Because by making the most of each piece of technology – working it as long as it delivers value, but no longer – is the most cost-effective business case.
There is no PdM without IoT. It’s that real-time data, from real-world sensors, that makes PdM possible.
Why it exists: key drivers for remote machine monitoring
Obviously, this makes cost a key business driver for PdM. Keeping assets performing for longer, with reduced downtime and avoiding equipment failure, makes your CFO happier – and your company competitive. But cost isn’t the only one.
Another is sustainability. Maximising each asset’s useful life is great for your recycling programme, and reduces your carbon footprint. With many governments now charging businesses fees and penalties for their CO2 emissions, there’s a cost advantage here, too.
A third, of course, is business continuity. IoT remote monitoring systems let you see likely equipment failures ahead of time, letting you repair or replace them before your users experience an outage.
There are also further opportunities for cost optimization. IoT remote monitoring can also show you where assets are under-utilised – letting you work those assets harder, or perhaps take them out of your cost structure. Ultimately, such small incremental efficiencies can make the difference between profit and loss.
But perhaps the biggest factor is having a Single Version of the Truth, or SVOOT. With the data from IoT sensors in every corner, combined with a data analytics platform to make sense of it all, your business (and the C-Suite) can see a total picture of your IT infrastructure, with all the right numbers and metrics taken into account. This provides an enterprise-wide picture of business risk – something investors (and customers!) really, really like.
IoT platforms by type: the 4 main options
But just as the web, email, and VPNs use different protocols and connection layers, there’s a variety of different methods for gathering IoT data and turning it into useful insights. They divide into four main platform approaches.
Cloud-based IoT platforms are lightweight and fast to deploy, often using trusted and tested third-party software developed specifically to collect data from IoT devices. The advantage is that technicians and users can see IoT data from anywhere; no local software downloads needed. And of course, they can scale to whatever size you need, fast. For this reason, cloud-based platforms are often used by SMEs.
On-premises platforms are in-house software. That means your maintenance team has to install, maintain, and manage a local solution – missing some of the advantages the cloud brings. It does, however, make security and access control easier – some of these “IoT” platforms aren’t even connected to the public internet, just to the IoT devices within a single building.
Hybrid platforms offer a mix. This is an approach Strypes favours: the right tools for the right job! Hybrid methods often mean using cloud-based IoT application for lower-level, less compute-intensive tasks like summing data from lots of small sensors, but in-house software on owned servers for applications needing high security or privacy protection.
Last comes edge computing. For large constellations of devices – perhaps millions of company badges, or a network of data centres, or remote retail shops – it often makes sense to process and analyse some data locally and some in the cloud. While many IoT devices aren’t data-intensive – a single sensor saying “On” or “Off”! – long distances between sensor and server can lead to latency problems, so there’s a business case for collecting that data more locally.
Applications and services: remote monitoring software
Of course, having this ocean of data available means nothing without software. And the best software today – the type Strypes uses – does far more than count bits and show graphs; it looks for patterns and probabilities in the data, using machine learning and artificial intelligence to predict what’s likely to happen in the days, months, or even years ahead.
This is the essence of PdM: the ability to visualise the future state of your IT infrastructure by looking at the picture today. It means your business, well, stays in business, with less downtime and more efficient use of resources. It means greater customer satisfaction, as you serve them smoothly and without interruption, with just the right amount of resources devoted to each job. It keeps your carbon footprint minimal because you’re using each piece of equipment for the longest time you safely can – and you’re using the data your sensors generate to plan for future equipment purchases.
In short, it’s about a lot more than just a cost case – although optimised costs are the first thing you’ll notice.
CONCLUSION: IoT monitoring is your enabler of PdM
That’s predictive maintenance with IoT remote monitoring. Whichever platform you prefer, Strypes can help you do it.
We plan and deploy IoT remote monitoring solutions for a huge variety of companies across Europe. Some of them operate machinery in complex environments like agriculture; others in the ultra-precise processes of clean rooms. But they all have a common purpose: understanding the state of their IT infrastructure … so they can make smarter, better-informed, more cost-effective decisions.
Ready to continue the conversation about how IoT remote monitoring and PdM can fit your business?
Remote Еquipment Мonitoring and Diagnostics for the Agriculture Industry
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