We were surprised at the results of our recent survey of compressed air users, which indicated a lack of urgency regarding digital technology, with only 24% considering Industry 4.0 and digitisation to be very important at the moment.  

This rises to 45% rating it as very important for five years’ time and 58% for 10 years’ time, suggesting that operators and owners consider Industry 4.0 to be a revolution of the future, rather than an area that can have a positive impact on their business performance right now.

In its 2017 report entitled, ‘Smart Factories: How can manufacturers realise the potential of digital industrial revolution’, Cap Gemini predicts that smart factories could add $500 billion to $1.5 trillion in value-added to the global economy in five years. It also claims that manufacturers predict overall efficiency to grow annually over the next five years at seven times the rate of growth since 1990 and that smart factories can almost double operating profit and margin for an average automotive OEM.

Despite the uncertainty evident in our survey, it is clear that Industry 4.0 is starting to take effect already, meaning compressed air users need to consider the opportunities it can present for improving performance, identifying inefficiencies and optimising equipment processes.

At the heart of this revolution is data and in the case of compressed air systems, the data that can be obtained and analysed to provide important insights in to ongoing system performance.

Basic data analytics, probably the most widespread form of analysis, collects data from various machinery and technologies, but this data may simply be used to remedy a particular machine issue during routine maintenance. It is a fairly typical scenario, whereby the compressed air supplier uses readings from various system parameters to carry out fault finding; fixing the issue and returning the compressor to efficient operating performance.

Maintenance

The next area that many end-users will also be making full benefit of is the area of predictive maintenance. Rather than scheduling service based on a set number of compressor running hours or, for example, an annual maintenance visit, predictive maintenance consumes data from the system to make intelligent assumptions about future performance. For example, readings from the compressor can indicate specific wear and tear on a particular component or consumable part, which may require replacement.  Analysis of compressor oils and lubricants can also provide insight in to machine performance and highlight where remedial action should be taken – preventing a minor problem leading to system failure.

Predictive maintenance techniques are already well-established however and, using the principles of Industry 4.0, some operators are now looking towards cognitive intelligence as the next step on their journey to improved efficiency. 

IBM explains Cognitive IoT as ‘the use of cognitive computing technologies in combination with data generated by connected devices and the actions those devices can perform.’

In short, the system ‘learns’ from its interactions with data and the end user interface. Not only does this require the ability to manage significant volumes of data, but for operators, and their suppliers, to implement robust and scalable management technologies. This is especially the case for businesses that have invested in compressed air technologies and ancillary systems from a range of manufacturers as there is the need to ensure that this data can interact, using an open platform.

Industry 4.0 is here and helping revolutionise the way that operators approach their compressed air system maintenance. From simple data analysis to all-encompassing cognitive learning, there is a solution for every compressed air user.