The smart route to reliability

Industry 4.0

The most notable development has been the advent and increasing adoption of Industry 4.0, IIoT (Industrial Internet of Things), and digitalisation, and the technological changes that this entails. One feature of Industry 4.0 that sets it apart from previous models is the convergence of information technology (IT) systems used for data-centric computing with operational technology (OT) systems used to monitor events, processes and devices, and make adjustments in enterprise and industrial operations to give a holistic view of the enterprise. Essentially, Industry 4.0 connects physical systems to the Internet and thereby enables high-value process data to be gathered and shared transparently from the system level right down to the sensor level. In practical terms, this puts preventative maintenance methodologies right at the centre of the smart factory, with the potential to transform the way equipment is monitored and repaired out in the field.

Using the IIoT, data can be gathered and displayed in real-time, and visualisation is not restricted to the machinery site or control station. Rather, all information can be made available everywhere – from smartphones to big screens, onsite or in the Cloud – and to a variety of parties from, for example, operatives on the plant floor, to technical experts outside of the organisation should the need arise. This also helps enable remote maintenance, which is particularly pertinent in the current climate of lockdowns and social distancing. The data can be gathered from a number of sources, for example, vibration sensors, acoustic sensors, temperature sensors, humidity sensors, power consumption monitors, and thermal cameras.

When it comes to analysing the data, using the right software, it is possible for production planners, process experts, and maintenance technicians to configure appropriate limit values and customised rules without the need for in-depth IT knowledge.

Machine learning also has a role to play. While many companies use a SCADA (Supervisory Control And Data Acquisition) system to collect data, create visualisations, support process control, and trigger alerts, there are drawbacks to this approach. Notably, they require people to configure systems to make them work as required. Moreover, the systems cannot spot anomalies in data, or predict a sensor reading in a specified time window. It is also incredibly difficult for a human operator to interpret data in real-time, which is seeing some companies now turning to machine learning instead.

Whereas a semi-manual approach tends not to take into account more complex dynamic behavioural patterns of the machinery or contextual data relating to the process as a whole, with machine learning, algorithms are fed OT data, IT data and process information. Then, in a process known as ‘training’, the machine learning algorithms detect anomalies and test correlations while searching for patterns across the various data feeds.

The digital twin

Central to many Industry 4.0 strategies, the digital twin can be broadly defined as a digital representation of a physical asset, system or process designed to detect, prevent, predict, and optimise through real-time analytics to deliver business value. With a digital twin, it is possible to ‘virtualise’ maintenance tasks with the use of digital renderings viewed using computers, tablets or mobile devices. This means engineers can gauge the condition, performance and history of the physical asset and make updates and amendments, without impacting with the physical asset itself. For businesses with remote assets, this can be of particular benefit.

It also helps enable businesses to determine the intervention and maintenance required to optimise asset performance and maximise its useful lifespan, before carrying out any work to the asset itself. This reduces unnecessary disruption and downtime, and also means the best-informed decisions can be made regarding the asset.

One of the most widely acknowledged benefits of the digital twin is its ability to simulate entire production systems and virtually test them without having to build a single physical element. Designs can be optimised and refined quickly and without incurring the cost traditionally associated with developing a new process. This also brings advantages when it comes to maintenance; as the digital twin replicates essential machines and production line activities, it is possible to train maintenance engineers how to take apart and repair equipment, in the right order, using the right parts, without impacting the physical asset. This is particularly pertinent for those industrial processes which incorporate high volumes of varying types of components.

Augmented reality

Another Industry 4.0-related technology that can be used to enhance the working lives of maintenance technicians is augmented reality, whereby wearable technology, usually in the form of glasses, headsets or helmets, enables staff to see 4D images above assets in-situ. These images can prompt via instructions and also give a mapping of asset functionality, enabling the user to access equipment information (instruction manuals, performance data, etc.) in real-time. Not only does this mean the engineer’s hands are free to work on the maintenance task, it can also help plug any knowledge gaps, the risk of human error is lessened, and work times reduced.

Although not strictly an industrial application, in an example of how augmented reality can enhance maintenance operations, Volkswagen Commercial Vehicles is rolling out augmented reality headsets for technicians across its Van Centre network to help speed up complex repair work.

The innovative system allows experts based at the Technical Support Centre (TSC) to send precise visual instructions remotely to technicians at Van Centres and Mobile Service Clinics to ensure any maintenance issues can be fixed as quickly and efficiently as possible, minimising the time a van spends off the road.

The nationwide rollout follows a successful trial that saved customers a year of downtime, equal to almost £250,000, with repair efficiency up by 93%. Not having to physically travel also meant a reduction of over 2.5 tonnes of CO2 for the TSC.

If technicians face complex or unusual servicing points – expected to be around 500 occurrences across the UK in any given year – they can use the technology to connect directly with the Technical Support Centre at head office in Milton Keynes. An expert is then able to support the field technician through the diagnosis and repair by augmenting images, wiring diagrams and adding repair suggestions into their view.

Maintenance-as-a-service

Converging with Industry 4.0, the expanding use of Cloud computing brings benefits in terms of capacity, scalability and performance. Cloud computing also allows the implementation of previously novel business models. Think of disruptors like Air BnB and Uber; similar trends are emerging in the industrial maintenance sector. Both industrial maintenance solutions providers and equipment manufacturers are developing Cloud-based ecosystems to allow them to deliver all the aspects of reliability-centred maintenance, as and when needed on a maintenance-as-a-service basis.

In the past, maintenance contracts have largely been based upon a flat service fee. Maintenance-as-a-service offers great value to the equipment operator, who is charged only for the actual use of maintenance services. In theory, it also means that the equipment provider will be motivated to provide the highest quality maintenance service, as well as the most reliable equipment – a definite win-win for the end-user.

Taking maintenance even further along the servitisation model, the sale of equipment will no longer be broken down into the asset and its maintenance, but the output of the equipment will be the metric by which the end-user is charged. In an example that is already a reality, aero engine manufacturer, Rolls-Royce offers a service whereby customers pay by the hour according to the amount of time an engine is in flight. Rolls-Royce essentially rents the engines to customers and then monitors data from the engines to predict potential maintenance problems, so maintenance work is only carried out when necessary. This saves costs on unnecessary maintenance, and also reduces unplanned maintenance and engine downtime.

Additive manufacturing

Another of the technologies closely associated with Industry 4.0 is additive manufacturing. In the context of maintenance, additive manufacturing offers a number of benefits. For example, using 3D printing techniques, it is possible to produce spare or replacement parts on-demand without the need for moulds, dies or pre-set tooling. This also means that changes can be accommodated without incurring additional cost, and batch-size one is easily catered for.

Today’s 3D printers are widely available and intuitive to operate. Suitable for use in a range of environments, from remote locations to the back of a maintenance technician’s van, they offer the ultimate in flexibility  – there’s a reason why the International Space Station has its own additive manufacturing facility in-situ!

Additive manufacturing is also a valuable resource when it comes to discontinued parts. Particularly in the UK, where assets are often worked beyond the originally intended lifespan, the ability to 3D print a spare part that is no longer available can avoid the need for costly equipment replacement, and help alleviate disruption to operations. There are also sustainability advantages, which are bound to become even more important in years to come.

Maintec

Taking place at the NEC, Birmingham, 3-4 November this year, Maintec is the longest standing exhibition dedicated to the maintenance, reliability and asset management industry, and will provide the perfect opportunity for visitors to discover the latest maintenance equipment and solutions.

https://www.maintec.co.uk/