Digitally driving compressed air performance

The fourth industrial revolution is driving every business to share and analyse asset data, and the IoT is showing no signs of slowing down. Indeed, IHS Markit forecasts that the market will grow from an installed base of 15.4 billion devices in 2015 to 30.7 billion devices in 2020, and then 75.4 billion in 2025.

With UK industry using over 20TWh of electricity every year to compress air, equivalent to the output of four power stations and over 8.1 million tonnes of CO2 emissions, high-quality energy and performance at a cost-effective price continues to be a key consideration for all businesses. Therefore, data-driven insights that can help achieve this are to be encouraged.

Generating compressed air accounts for 10% of total energy costs in industry, so ensuring wastage is kept to an absolute minimum should be a key concern for all operators. And with industry averages suggesting energy costs account for more than 80% of the total cost of ownership of a compressor, any initiatives that can help companies identify inefficiencies and assist with performance optimisation, leak reduction and practical air management processes will be welcomed. Industry 4.0 and the IoT are, without doubt, the greatest opportunities available today to help organisations work smarter.

Many organisations do not have the time or resources available to make the most of the data and information they collect. Alternatively, the trend seems to be to only consider data when an issue arises, rather than using it to effectively manage a compressed air system on an on-going basis.

Stages of analytics

There are three key stages to analytics. The first is as simple data, outlined above, which is where data is collected but not processed in any meaningful way. Most of the world’s digital data is unstructured, and therefore lacking value.

The next phase is predictive, whereby analytical tools are used to ‘consume’ data. This will then make predictions about unknown future occurrences, using a range of techniques such as data mining, statistics, modeling and machine learning to do so. ‘Edge analytics’ is a key term within this context too, essentially referring to an analysis that is performed at the point of data being generated.

When based upon logical and intelligent rules, predictive analytics can give businesses the right information, when needed. For the IoT to truly be successful in the compressed air market, businesses will need to work collaboratively with an informed and knowledgeable organisation that has the in-depth understanding to establish the right rules within a system. These are the rules that will provide valuable insights into how a compressed air system is running and offer recommendations into how its operations could be optimised and improved.

The final stage is cognitive analytics. This is a strategy that describes how analytics and technologies can be applied to help humans make smarter decisions. A cognitive system will learn through its interactions with data and responses from the end user. It draws inferences from existing data and patterns; draws conclusions from existing knowledge bases; and then learns from this to inform future decision-making and business intelligence. And because a cognitive system is in a perpetual state of learning, it will keep adapting to deliver the required outcomes in the most efficient way possible.

Cognitive analytics is a true blend of human and artificial intelligence. These systems learn automatically, helping to improve a business’ productivity, efficiencies and – as a result – the overall customer experience. The potential for this level of insight is really exciting, as it is technology that will automatically learn from past data and experiences, creating new systems as a result. This is the kind of smart digital future Gardner Denver is championing for the compressed air industry.

Modern iConn

To meet this need, Gardner Denver has introduced a new digital platform, iConn, to the market. This is a cloud-based, air management platform, which has been developed to deliver advanced analytics, enabling operators to stay in control of their installation. The system provides historic, real-time, predictive and cognitive analytics, allowing users to rectify potential issues before they happen.

The platform is particularly beneficial for businesses with multiple remote sites or unmanned installation, as it enables users to monitor compressor performance from a single location, via their mobile device, tablet or PC.

iConn helps minimise fault incidences for increased uptime, and also provides detailed machine parameters and over-time trend analysis to enable plant managers to optimise system performance.

Compressor or ancillary asset data can be transferred securely via GSM, Ethernet or Wi-Fi, to a wide range of connected devices, ensuring data security. iConn’s cloud-based services also allow users to view real-time analytics or access data through open APIs.

There is also the option for Gardner Denver’s experts to access the information to help customers make informed choices around compressed air optimisation, maintenance schedules and energy performance.

An open future

One of the biggest changes to the IoT in industry is the move from closed, proprietary mechanisms to open ones. Gardner Denver is assisting organisations with systems integration, helping information technology and operational technology work together.

While iConn is available as standard on all new CompAir machines and can be retrofitted to existing compressor installations, a key feature throughout its development has been the fact that the platform also supports ancillary and non-Gardner Denver based products. The aim is to provide a one-stop digital experience for managing an entire compressed air system.

Most customers, over the years and various product lifecycles, will have purchased from lots of different brands. iConn, however, is not intended to be solely a Gardner Denver based system. Indeed, other data provides richer insights into the quality of a compressed air system. Like the IoT, which has been successful because it’s been disruptive, iConn’s aim is to create a service that will provide truly meaningful insights no matter who manufactured the technology.

For those seeking a smart manufacturing strategy, data analytics offers organisations the most valuable means of evaluating compressed air generation yet available on the market, helping professionals to manage, optimise and improve usage.