our stories

tech never sleeps, so neither do we

tech world

Bridging the gap from IIoT promise to IIoT reality

With any new technology innovation, we can expect to follow Gartner’s pattern of adoption to some greater or lesser extent.

First comes the technology trigger, then the peak of inflated expectations, through the trough of disillusionment, then upwards to the slope of enlightenment and, finally, we reach the plateau of productivity.

The growth of the Internet of Things

The Internet of Things – the network of connected devices which characterises our modern lives – is expected to have grown to 64 billion connected devices by 2025, according to a Fortune Business Insights report. It expects the overall IoT market to be valued at one trillion USD by 2026. Since its value stood at USD 190 billion in 2018, this puts the IoT’s annual growth rate at 24.7 percent.

Such numbers suggest that the hype of the IoT promise has not in any way been overstated. However, when we think qualitatively about the delivery of the promise, it sometimes feels like a very different story…

The promise of the Industrial Internet of Things

The promises of the Industrial Internet of Things (IIoT) were many and varied. They included: preventative maintenance programmes which reduce manufacturing downtime; enhanced overall equipment effectiveness which improves profitability; seamless supply chain integration for more efficient and flexible collaborations between partners and greater efficiency and sustainability; and more.

Skyquest data puts the global IIoT market value at USD 102.48 billion in 2022, with an annual growth rate of 7.2 percent expected between 2024 and 2031. While impressive, the growth rate falls significantly short of the IoT growth as a whole.

Indeed, estimates suggest that in the manufacturing sector, only 14 percent of machines on shopfloors are currently connected. There seems to be a big gulf between the vision of industry thought leaders and the reality on the shopfloor.

Why is there a gap from IIoT promise to IIoT reality?

Every solution first demands an understanding of the causes of the problem. When thinking of how to bridge the gap between IIoT promise and current IIoT reality, a better first question to ask might be: what is the cause of the slower adoption of IIoT than the overall IoT trends?

First, manufacturing environments must deal with a much greater degree of complexity, not least in terms of safety, security and regulatory obligations as well as the heterogeneity of existing technologies around the plant. These come in addition to considerations of quality and profitability, which probably don’t come into play when you plug in your Nest doorbell or new Echo Dot.

This complexity has been exacerbated by early encouragement by IoT solution providers for manufacturers to “start small” and to test and iterate. This has resulted in a good deal of extra systems and technologies dotted around the plant – further adding to the complexity with which manufacturers have to deal.

What’s more, too many early projects have failed to deliver and this, combined with the extra technology management overhead, has precipitated a (relatively shallow) decent into the trough of disillusionment for some.

Overall, the promise holds strong – but to deliver on the real promise of the IIoT, these multifarious systems require bringing together into a homogeneous whole from which a picture of overall performance can be gleaned.

How do we bridge the gap between IIoT promise and IIoT reality?

Getting data from old machines is a real problem. While we can retrofit a certain number of meters or devices, it isn’t always possible to retrofit solutions which gather the exact datasets required.

As machines retire and are replaced by newer machines with integrated sensors and metering, the picture improves. Newer machines offer modern connectivity options and meet today’s standards for cyber-security.

However, production machines are expected to enjoy long lifecycles. A rip and replace approach is not financially feasible or desirable in most cases. Instead, we need to look to integrate new components in a modular way. The Module Type Package (MTP) standard is a major step forward for plug-and-produce manufacturing and offers a sensible way to futureproof equipment more successfully.

In addition, we need to look to integrated data platforms which allow data to be pulled in from diverse data sources around the plant, where it can be combined, consolidated, analysed and presented for review. Cloud environments such as Microsoft Data Factory, which allow integrated artificial analysis tools to be applied to the data, offer one option for advanced data integration and subsequent AI-powered analysis.

Realising the promise of the IIoT

There isn’t one right answer to solve the problem of the IIoT promise-reality gap. Open connectivity standards and cloud-based data platforms with integrated advanced analytics and AI tools will help – but to implement these solutions effectively will require a rethinking of skills. It demands a convergence of traditional IT and plant IT/ engineering activities as well as the development of new competencies in the associated cloud and data infrastructures, advanced analytics and AI capabilities.

← Previous Story Next Story →