Getting ready for the next industrial revolution

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 nearly double operating profit and margin for an average automotive OEM manufacturer.

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.

The Internet of Things (IoT) concept

One definition of the IoT is that it ‘allows objects to be sensed and controlled remotely across existing network infrastructure, creating opportunities for more direct integration between the physical world and computer-based systems and resulting in improved efficiency, accuracy and economic benefit.’

The manufacturing sector is seen as a key beneficiary and, with compressed air energy consumption representing as much of 10 per cent of all electricity consumed by industry, there are tangible efficiencies to be realised. Already, sophisticated robotics are being introduced on the factory floor, and smart components can communicate assembly instructions to the production line. 

The challenge for equipment suppliers now – and compressed air systems producers are no exception to this – is to move beyond the theory and the conversations to practical application.

Increasing connections

Adding data intelligence to air compressors is not a new concept. There are already many thousands of connected compressors operating across the globe, which are enabling engineers to analyse performance patterns and apply this understanding during the design and development of new compressed air technologies.

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.

More recent advances have enabled compressor controllers to be connected to mobile devices through systems, and this facilitates remote monitoring over a secure network. Operators can keep track of key parameters including pressure, flow, and motor and dryer speeds, and then make adjustments when necessary via a compressor’s manual interface. This ability enables varying production demands to be accommodated and helps plant managers improve efficiency and save energy.

Monitoring and insight

The application of connectivity and remote condition monitoring technology is helping to enhance best practice in operations between compressors and the wider smart factory.

During this process, data is gathered, compared and analysed. When required, warnings can be sent out in order to prevent downtime, and to enable local service providers to remedy any issues.

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.

Cognitive intelligence

Some operators are now looking towards cognitive intelligence as the next step on their journey to improved efficiency. 

Here, the system ‘learns’ from its interactions with data and the end user interface, requiring operators, and their suppliers, to implement robust and scalable cloud-based management technologies.

Progression towards full remote or automated control of compressors is certainly on the horizon as more and more data comes ‘on-line.’  This will not eliminate the role of the compressor operator as there will still be a vital requirement for a human interface between compressors and the wider smart factory environment.  

Smart data is here to stay and BCAS and its members are working hard to develop compressor technologies that can take full advantage of the opportunities it presents for improved efficiency, increased uptime and ultimately, bottom line profitability.