In this our fourth article on Predictive Maintenance, we look at how predictive maintenance techniques can set your business on the path to asset management maturity.
Predictive Maintenance, as we’ve seen over the last three articles, uses analytics to predict an asset’s condition, future reliability and general maintenance requirements. And we also know that maintenance increases the availability and longevity of assets and generates revenue.
I don’t know how many readers of this article were fans of IT Crowd, the British comedy series from the late 2000s, following three staff members who work in the IT department of a fictitious company. The show is responsible for phrases that are now well and truly part of our vernacular, such as ‘Have you tried turning it off and on again?’ But one of my favourite episodes of the show relate to Google. It’s where Jen says, ‘If you type Google into Google, you can break the internet.’ Of course that can’t happen and Jen’s co-workers, Moss and Roy, knew this all along.
Thank you for joining the Asset Management Council in our third article on predictive maintenance. In our previous two articles, we gained an understanding of what predictive maintenance is, and data’s role within it. Today, we follow on from the latter, with a specific example in Melbourne.
If anyone reading has ever been on a tram in Melbourne, you’ll know the network is extensive and reliable. As a tram ambles along its tracks, most passengers have their heads down staring at their phones, or nodding off to music. Some on board might be alert for Myki inspectors, ready to clamber off to avoid a fine. Given these distractions, many on board would be unaware of how the smoothness of the tracks or weeds sprouting along the track might impact a tram’s journey.
We are all connected: to each other, to our devices, and to a vast number of systems within the government and private sectors. This is quite obviously due to the arrival of the Internet of Things (IoT), those wearable and portable devices that connect us to the internet. Such gadgets yield copious amounts data, and present both huge challenges and fabulous ways to build value. Known as big data, it has totally revolutionised the way many businesses and organisations operate.
Throughout the month of December, we’re taking a closer look at predictive maintenance, with an article each week to showcase its importance in relation to asset management. If you missed the first one you can find it here, or read on to enjoy our next thrilling instalment.
As noted in our first article, predictive maintenance is all about forecasting future failures in your assets. In other words, predictive maintenance offers a view of what was previously unseeable, and therefore take maintenance operations to the next level.
That’s all very well, but how is predictive maintenance best implemented? The answer lies in data.
You can’t be in the contemporary world and be unaware of data: its volume, its importance, and its pitfalls. Whenever we download an app, or buy something online, or even just sign up to a newsletter, we are giving the business our personal data. That business then has the opportunity to leverage that data to its own benefit.
Take Google, for example. The powerhouse began as a simple search engine in the late 1990s, but has woven its way into knowing every aspect of our lives: job searching to dating, where we travel and what we buy. The data—to say nothing about the huge breach in privacy currently being investigated by the ACCC—held by Google is beyond anything we can possibly imagine.