Develop a data-led decision-making process using IIoT

Plugging into the right data can help you to tackle production and maintenance problems before they even emerge – but learn to walk before trying to run

The Industrial Internet of Things (IIoT) relies on data – and most industrial settings are full of data if you know where to look. However, while a lot may be available or easy to harvest, the real challenge is to collect and collate data in a structured way.

Why? Because a flood of data streaming in from various data-enabled assets and sensors is not in itself especially valuable. The real purpose of IIoT is to integrate and analyse the relevant data, generating insights that you can draw upon to make evidence-based, data-led decisions that will improve production and maintenance within your facilities.

Here are three steps to help you reach that end goal.

Find your data

Scientists and engineers have long known the value of gathering data. As the pioneering nineteenth-century mathematical physicist Lord Kelvin put it, “To measure is to know. If you cannot measure it, you cannot improve it.”

To measure in an industrial setting, however, you first need to know where the data is – and there are typically three key sources.

1)?????Stranded and siloed data

This data is in the factory environment but it’s typically locked in a machine by an OEM, making it challenging to integrate with other business platforms and applications

2)?????Untapped data?

This data is in the factory but it’s not being used. Examples include data within existing machines such as inside inverter drives or process control systems

3)?????New data

New sensors, actuators and other end-point devices that allow for the real-time collection of data

Existing data flows within factories are often single-purpose vertical flows dedicated to a specific process or asset but unlocking their full value requires horizontal integration with other systems and devices – often being repurposed for different objectives.

This is what creates a truly connected factory, although initial IIoT implementation doesn’t need to be so complex.

Solve a single problem first

IIoT implementation can begin with just one application.

Don’t think that you must introduce IIoT across your entire facility then find problems to solve once you have the resulting data. Instead, start small with a single problem that has traditionally been difficult to solve.

“We often say to our clients, ‘Look for the problem that keeps you awake at night, then see if IIoT can break the impasse,’” explains Richard Jeffers , founder and managing director of RS Industria, a modular, plug-and-play IIoT platform.

Take a vibrating pump. While all pumps vibrate, you may have noticed that one is vibrating far more than it should. Simply knowing there is excessive vibration won’t provide any answers – you need to understand the cause and how significant it is.

An IIoT implementation focused on this single process can analyse the data coming in from sensors to reveal insights into whether it is a mechanical or hydraulic problem. The sooner this problem is identified, the sooner action can be taken and costly downtime prevented. Further value from IIoT can be extracted when the data is not only analysed to assess machinery performance but used to predict potential future failures.

“With the vibrating pump, you can take the view that above a certain temperature or vibration level, a piece of equipment needs to be shut down,” says Jeffers. “But IIoT now enables you to predict that a particular piece of equipment might be about to reach those levels before it happens.

“You’re now at a point where you can actively make decisions and drive continuous improvement based on insights from your data. And once the benefits are realised from one project, you can expand the IIoT system to other assets and processes.”

Develop ambitions as you go

As this example demonstrates, it’s not about big data but the right data – and often a little can go a long way when it comes to generating insights that lead to practical and cost-saving benefits.

With a plug-and-play approach to IIoT, as offered by the RS Industria modular platform, users can start with low cost, low risk projects such as this and then broaden their ambitions over time.

This is the approach that Jeffers encourages. “Rather than thinking of it as a single overwhelming project, industrial organisations need a structured approach to tap into their data,” he advises, “Collecting it in a planned and modular way.” ?

For more on gathering data from existing equipment, download our guide here.

A version of this article originally appeared on RS Industria