Augmented Reality set to take maintenance to new heights

David Lincoln

August 23rd, 2021


David Lincoln

Digital Lead, Measurement & Analytics


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Augmented Reality promises a step change in the way process industries think about maintenance. With real time help from human experts or automated systems, AR supercharges the already formidable power of Predictive Maintenance. David Lincoln, Digital Lead for ABB Measurement & Analytics, explains how.

In the realm of digital technologies, Augmented Reality (AR) certainly stands out. Overlaying digital data on what you are seeing in the real world, rather like the head up display in a combat aircraft, has uses that really jump out – as well as the obvious ones in gaming and entertainment, it is finding applications from surgery and healthcare, to fashion and retail outlets.

Closer to home, industrial applications are not being left out either – one of its biggest uses is expected to be in Predictive Maintenance (PM).

Using data from devices or processes to detect trends or analyse patterns, to predict when an asset will need servicing.

The result is better, more planned use of your maintenance staff, a minimum of lost production and lower costs.

PM is already a game changer. Many processes still rely on disconnected devices, offering no monitoring of diagnostics at all. The most operators can expect is an alarm to indicate that something has gone outside its normal range – depending on the severity of the problem, the device might just stop communicating or cease working altogether.

When the operator realises that the device is not working, they will call a field service centre, who spend further time to identify the device and provide details of it. The result is that someone is dispatched to site with no knowledge of what the problem is and whether they have the right parts to do the fix.


Next level maintenance

With its power to identify when you need to do something, PM is increasingly essential - either manually using people’s expertise to define a problem and when it will occur, or automatically using analysis of data.

AR in the context of Predictive Maintenance is part of the growing move towards autonomous systems - a device being monitored and a problem being detected within or around the device automatically. The root cause of the problem is automatically worked out, the timeframe within which a problem would occur is calculated and the way to perform the fix automatically provided.

AR can be operated in two ways, in either a manual system or a fully automated system. A manual system would involve an expert, who guides the engineer through the process via a remote channel and describes how to make the fix.

In a fully automated system, the AR would be driven by the AI prescribing what the problem is – it would then provide the user with the procedure and process, presenting instructions and maintenance information graphically via an iPad or some type of projecting lens.

The system may also automatically despatch a spare part if required.

Options for the fix

When it comes to fixing a problem, there are essentially two scenarios. The first is where the customer carries out the work. In this scenario, the spare part is automatically despatched, and the customer is informed how to do the fix.

Alternatively, the PM solution creates a case which is automatically filled by an ABB service engineer, who is provided with the part and goes to the site with an AR app and performs the task.

Using AR and its supporting applications and systems has two major benefits. The first is a reduction in the number of touch points that can potentially go wrong. This way of working also moves the plant from a situation where events are uncontrolled or unscheduled, to one where we have a plan based on the knowledge that certain components will need to be repaired or replaced at a particular time.  The PM approach reduces the time needed to get a plant back into operation and improves safety by not putting the plant into an unknown condition.

AR also enables remote working. With the COVID pandemic, the ability for technicians or engineers to be supported by a remote live expert or fully digitized teaching tools, is a major advantage and contributes to getting systems back online as quickly as possible.

Surmounting the barriers to AR

As issues such as skills shortages, remote locations and staff absence affect the ability of companies to keep their systems up and running, AR is set to become increasingly common. Many countries have plants that are difficult to get to and even well-populated countries have their share of remote locations.

There will most likely be a combination of factors that will drive the adoption of AR - the way that different generations access information and use devices, shifts in behaviour and technology will all contribute. We have seen technology go from disconnected devices to connected, then move from monitoring to condition monitoring, then to predictive maintenance as people understand what the data is showing them.

The most recent development has been prescriptive. This is a fundamental part of the AR concept, with applications explaining what you need to do - ultimately, we may well see a move to autonomous maintenance, with the fix itself even being automatic, possibly even self-fixing devices. In some respects, SIL safety protocols are about looking at failure mechanisms within systems and having built in redundancy, so you can deal with unplanned errors.

Eventually, redundancy may well be virtualised, with software based virtual flow measurement that allows you to infer flow even when your flow installation stops working you, in a similar way to digital twinning.

Once we overcome the barriers to its adoption, making it easy to use and widely accepted by industry, AR is bound for a big future as part of the maintenance landscape of process plants – with its promise of faster, easier fixes, saving time, money and effort, it can’t fail to play a significant role in improving efficiency and safety.

Unleashing the true power of prediction

Developments in technology are offering greatly expanded potential for predictive maintenance to help transform the performance of production processes. By providing operators with advance warning about issues and problems before they occur, together with the information needed to fix them, the combination of predictive maintenance and tools such as Augmented Reality provide a winning formula for achieving improved efficiency with greatly reduced downtime.

For more information, including how to download our Remote Insights AR app, visit

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