Key Takeaways

  • Hand holding dollar icon

    Predictive maintenance is helping industrial sectors to go beyond simply preventing equipment breakdown. By using digital technologies to reduce the likelihood of failures, it helps operators avoid costly downtime and high maintenance costs.

  • Liquid is dangerous icon

    Oil condition monitoring is one way of shifting from a reactive to a proactive – and preventative – maintenance approach, with continuous testing and oil analysis helping to spot potential issues before they occur.

  • Remote sensors icon

    Remote sensors and real-time oil analysis programmes allow operators to take the next step towards predictive maintenance to ensure equipment health – with machine learning and advanced analytics combining with human expertise to enable faster decision making based on real-time insights.

  • Digital equipment icon

    Digital equipment management platforms give off-highway operators the ability to track large vehicle and equipment parcs, collecting data on everything from fuel consumption and emissions to idling time and utilisation – all in one centralised dashboard.

History is full of examples of society imagining what the future will look like. From flying cars to robot helpers, every generation thinks they can predict how the world will change over the next fifty to one hundred years.

These projections often have one thing in common: they tend to focus on the consumer lifestyle as opposed to the industries behind the individual. Industries like construction, manufacturing, mining, and power meanwhile, carry on moving forward, often out of sight and out of mind for much of society.

However, take a closer look and this is arguably where the real technological breakthroughs have been taking place over the last few decades. None more so than predictive maintenance – an approach to maintenance management that uses data to forecast the optimal time for intervention, with an insight-driven regime rather than one based on a pre-set schedule. Importantly, this approach is helping to equip industry teams with the tools needed to fully realise their business’ operational potential.

Oil condition monitoring: Setting the foundation for predictive maintenance

While seeing into the future has proven to be a difficult task for most, it’s actually something that is becoming a lot more common within many industrial environments. Starting with oil condition monitoring (OCM) – a maintenance programme that uses various oil analysis tests to provide operators with early warning insights into the health of their equipment.

Shell LubeAnalyst is a good case in point: a lab-based oil analysis programme, it tests everything from contamination to viscosity in order to build up a comprehensive picture of oil – and equipment – condition. With 30 years of in-service performance benchmarking data, equating to roughly 25 million data points, the resulting reports can provide an indication of potential issues before they even occur.

And because the future holds a different outcome for each individual business, Shell continually invests in innovative technologies to meet a variety of maintenance needs across a number of industrial sectors – helping operators make the most of the data available to them. Take the power sector, for example, where only 20-30% of data collected in plants is currently used to directly inform decision making; a service like Shell LubeAnalyst prevents operators from overlooking valuable insights that could guard against significant losses.1

Real-time oil analysis: Where 'man' meets machine learning

The true merging of digital technology and the human mind might still only be a work of fiction, but that doesn’t mean the two can’t work together in harmony across today’s industrial landscape. In fact, the combination of human expertise and the power of data is becoming an increasingly important tool for those looking to maintain nimble and efficient operations.

“Real-time oil analysis allows you to enjoy your morning coffee while your oil is monitored remotely.”

Shell Remote Sense epitomises this meeting of minds, by combining more than 30 years of lubricant expertise with advanced analytics and machine learning. And thanks to sensor technology, this combination helps deliver actionable, real-time insights into the condition of in-service oil, giving you access to its live, round-the-clock status. Since this avoids the need to send away samples to the lab and wait for the results, you can instead enjoy your morning coffee while your oil is monitored remotely.

With 44% of power sector staff admitting that maintenance is not prioritised until equipment breaks down – and 40% often experiencing breakdowns due to ineffective lubrication – the value of this data-driven process can be huge.2 That’s because Shell Remote Sense allows operators to act more quickly on immediate insights into areas such as Remaining Oil Life and Contamination Detection, maximising uptime while quantifying CO2 savings from optimised lubrication.

This kind of predictive maintenance is helping industrial sectors to go beyond simply preventing equipment breakdown. By using digital technologies to reduce the likelihood of failures, it helps operators avoid costly downtime and high maintenance costs – helping to potentially reduce overall maintenance costs by 5-10%.3

“Shifting to predictive maintenance can help reduce overall maintenance costs by 5-10%.³ “

Digital equipment management: Tracking equipment from any location

Stationary assets are one thing, but what happens when your most important – and expensive – equipment is constantly on the move and exposed to external variables like unpredictable weather and uneven terrain? Again, the answer involves sensors. But this time, the data pool is expanded to address mobile needs like fuel consumption, idling rates and emissions output.

That’s why a tool like MachineMax relies so heavily on the Internet of Things (IoT). By allowing operators to connect their off-highway equipment to their chosen digital platform, the resulting exchange of data can help maximise productivity, and therefore, profitability too. Take idling for example: beyond its environmental impact, eliminating idling from your company’s work vehicles has the potential to save almost $15,000 per vehicle each year.4

And that’s not all. Using MachineMax’s digital telematics solution, a business is given greater visibility into the makeup of their vehicle parc, whether owned, rented or contracted. Armed with a wealth of real-time data, a raft of strategic decisions can be made with confidence, such as:

  • Adapting the size or composition of the fleet
  • Removing bottlenecks and increasing utilisation
  • Automating servicing schedules and proactively managing maintenance

The best way to predict the future is to create it

Even in the 21st century, predicting the future is still not yet a science. However, thanks to advancements in digital technology and industrial expertise, predicting your maintenance needs is a lot more achievable, providing you have the right tools at your disposal and the technical support to guide you there. Shell Lubricant Solutions combines both, by facilitating partnerships that are helping business and society to progress more quickly, while continuing to provide maintenance solutions that prioritise the performance and protection that industrial operations continue to rely on.

1Rodolfo Maciel and Peter Safarik. “Power Plant 4.0: Embracing next-generation technologies for power plant digitization.” McKinsey & Company. September 2020 (accessed 20 May, 2022).

2This survey, commissioned by Shell Lubricants and conducted by research firm Edelman Intelligence, is based on 350 interviews with Power sector staff who purchase, influence the purchase or use lubricants / greases as part of their job from March to May 2018. For more information, please visit (accessed 20 May, 2022).

3Chris Coleman, Satish Damadaran and Mahesh Chandramouli. “Making Maintenance Smarter.” Deloitte. 09 May, 2017 (accessed 20 May, 2022).

4Volta Power Systems. “The true cost of idling for work trucks.” June 12, 2020 (accessed 20 May, 2022).

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