As part of our increasingly connected world, companies are now able to use technology to manage their assets more efficiently, which has led to the rise of predictive maintenance (PdM).
How can predictive maintenance help protect assets?
Predictive maintenance (PdM) – which is aimed at reducing the likelihood of failures and, as a result, avoid costly downtime and lower maintenance costs – comes to the fore when companies address asset management. PdM can be implemented by monitoring the condition and performance of equipment during its normal operation, and using sensor technology and computerized maintenance management system (CMMS) software.
Alongside the sensors, PdM software can access a number of different data sources in real time, which can then predict asset failure or quality issues. These solutions use predictive analytics to detect any anomalies and failure patterns, determining where any problems or failures are likely to occur.
Dirk Claessens, IBM managing director for its Royal Dutch Shell account, explained how this technology all comes together in real-world applications, saying: “The objective is an increase in reliability of the overall asset or part of the asset.” “The predictive part is not just taking data from the automation piece, but a whole host of data: it could be maintenance logs, weather data, production forecasts and so on.”
“It’s all about reliability. Depending on where you come from – whether you are an OEM manufacturer equipment supplier or an owner operator – you will have a different viewpoint.”
Claessens also explained how owner operators tend to be more interested in reliability in the overall operation, with the result that they’re more interested in how the maintenance service orders affect the overall production performance. OEMs, on the other hand, are more interested in becoming more efficient and effective in the machine itself. This is a more limited scope, in order to provide a better service to their clients and isn’t necessarily tightly integrated with the overall planned performance.
Are there cost savings to be made?
The cost of that increased reliability is not to be discounted, either. A McKinsey Global Institute report, The Internet of Things: Mapping the Value Beyond the Hype, suggested that manufacturers’ savings from predictive maintenance could globally total between $240 and $630bn by 2025.
That’s a lot of money, which makes academic research into predictive maintenance a worthwhile investment.
Professor Julie McCann, from London’s Imperial College, is one such academic. She and her team have been studying how PdM systems are being adopted in industry – and how they can be improved: “Sensing has been in industry longer than trendy terms such as IoT.”
The vibration sensors that have previously been used, stretching back to the 1950s, in some cases, are wire-based sensors and quite expensive, which meant that they were used sparingly.
McCann added: “What we’re seeing at the moment is the lower cost price per sensor and the delivery mechanism has become wireless – which means you can place sensors in more awkward and difficult-to-get-to areas. Technology is now more fitting to be able to place sensors around and monitor these kinds of systems. And the cost benefit now is much more favorable to ship these systems with the sensors in them.”
To read the entire article by Shell Oil, click here.
