By James Blackman October 3, 2024
In researching a new editorial report, out this month, about the state of private 5G in Industry 4.0, RCR Wireless asked around about the biggest impediments to make enterprise-owned 5G scale in industrial venues. Among the responses, Nokia and Siemens separately compiled a list of five blockers, as of today, to its easy sale and scale. Their answers matched, more or less; and have, in turn, been crossed and compiled into a single list – of six barriers to scale.
Here they are; the quotes are from David de Lancellotti, vice president for enterprise campus edge sales at Nokia, and Daniel Mai, director of industrial wireless communication at Siemens. Note, this article works as a short excerpt from the upcoming report, and a preview of a webinar next week (October 10) on the same subject; its themes will be explored in more depth in both. In the meantime, their answers offer a neat overview of the challenges in the market.
Sign up here to join the RCR Wireless webinar on how to scale private 5G in Industry 4.0 (‘balancing customisation and simplicity in private industrial 5G networks’) on October 10, featuring speakers from CCS Insight, Ericsson, EXFO, and Verizon Business.
1 | SPECTRUM
Always and forever, cellular technology is about spectrum; its local availability for enterprise usage in certain markets was the single biggest driver to open the private 4G/5G market in the first place. But it is a finite resource, and it remains scarcely available. “Spectrum for the use of private networks is not yet available in all countries,” says Mai. Indeed, the private 5G market is largely concentrated in North America, Western Europe, and parts of Asia Pacific.
There are yawning gaps in-between, and even within – where regulators are yet to liberate spectrum directly to enterprises. Big mobile operators remain the gatekeepers for licensed cellular spectrum in these geographies, and, even as they work variously to deploy private networks in local tranches of their own 4G/5G bands, the global picture is fragmented. Easy scale hinges on global standardisation of local enterprise spectrum.
Mai notes “first steps” (“partially implemented”) by the European Union, at least, to “equalise” usage of the 3.8-4.2 GHz band for private 5G across the bloc – as the UK has already pioneered, and as certain EU member states have already prepared. But regulation is a slow process, invariably, and the planet is big. So progress to establish globally standardised spectrum for private 5G will come in fits and starts, and probably never be finished.
2 | DEVICES
Ah, devices; it’s always devices – either unavailable or too pricey. Such is the novelty of 5G technology, unravelling in the market in phased 3GPP releases, and such is the schedule of industrial equipment, rolling into market on decades-long upgrade cycles, that the crossover ecosystem for industrial 5G devices was never going to be quick. Mai comments: “Industrial 5G is a new technology, and the ecosystem doesn’t exist yet – and will only develop gradually.”
As such, all the nitty-gritty industrial IoT that was flagged for ‘massive’ 5G connectivity in Industry 4.0 as part of the original 5G hype narrative remains futuristic. “Certain end devices and thus applications are not yet possible – such as for a wide selection of smart tools,” says Mai. Nokia says the same about devices, citing a “lack of standardisation”. The problem has been so acute that Nokia has been forced to develop its own industrial 4G/5G devices
These include ruggedised handhelds, wearable cameras, speaker microphones, and helmet-headsets – designed for “harsh environments… [and] validated for high performance,” says de Lancellotti. But even as connected-worker solutions come available, and big-ticket AGVs and AMRs get connected, and even as smart tools and componentry go into production, they come with a premium, initially – which has to be worked into the original business case…
3 | VALUE
The bottom line, then: how to make money back. Mai at Siemens comments: “In industry, efficiency is the most valuable asset. Companies want to make sure that new technology is reliable and offers added value. Successful references from early adopters will lead to greater dissemination here.” The point is that the ecosystem should work harder to promote and share its successes – about how private 5G has raised efficiency and productivity.
Maybe even, how it has inspired innovation; and crucially, how these various upsides map to financial performance. Of course, the Industry 4.0 market is fragmented across sectors and competitive within sectors. Different industries have different priorities, and similar enterprises in similar industries rarely divulge their advantages. Architectural blueprints offer value, to streamline deployments, but clearly-plotted use-case references stand out for enterprises.
Beyond, there is a challenge to make private 5G more affordable – or just to make it more palatable. De Lancellotti at Nokia cites “high initial deployment costs” as a barrier. To an extent, these can be misunderstood, initially – on the grounds cellular requires less hardware than Wi-Fi, say, and delivers more performance. But Nokia has also shrunk its DAC private 5G system down for smaller deployments, repeatedly, and also bundled it into a subscription.
He says: “We have addressed [initial deployment costs] with our as-a-service model, and by adapting our DAC solution to smaller sites, and also by bundling [with compute hardware].”
4 | SYSTEMS
Or IT/OT integration, in straighter terms. This is a gnarly issue; for context, both Siemens and Nokia consider private 5G to be an OT discipline, primarily – to be commanded by technicians on the shopfloor, as part of critical production systems. Which is hardly in dispute; Industry 4.0 is an OT-geared domain, after all. Neither do they contest the importance of IT integration on the ‘northbound’ side – if specialist OT systems are to mesh with standard IT functions.
But there remains a wider debate – magnified until it is resolved – about who holds sway in the management of industrial 5G devices and applications, and therefore of industrial 5G networks. Other vendors appear, philosophically, to side with the IT crowd in their pursuit of private 5G sales. This will be explored further in the upcoming report, and divided into two different integration challenges. But they are conjoined in the responses from the two firms, here.
Nokia cites “complexity of integration with IT/OT systems” as a barrier to scale. De Lancellotti points to its work with role-based access and security controls, as well as with northbound IT and cloud connectors. Mai at Siemens hints at cultural issues with IT/OT in enterprises. He says: “The integration of OT and IT is not clearly regulated in many companies. 5G connects both systems, so responsibilities must be clarified in enterprises – which often leads to delays.”
5 | SECURITY
Quickly, a couple of final barriers-to-scale – and the only places where Siemens and Nokia differ on their lists (even if both would acknowledge each others’ entries). Siemens rounds-out its top five with a defining Industry 4.0 challenge: cybersecurity. If it’s not secure and reliable, it is not going to fly – is the message. Mai says: “Cybersecurity is essential for industrial companies. For a new technology like 5G, reliable concepts must be developed [for it] to be securely integrated into corporate networks.”
6 | SKILLS
Meanwhile, Nokia puts a final focus on skills and staff. De Lancellotti says: “Limited expertise and skills [within the Industry 4.0] workforce is both a barrier and an opportunity.” And while there are issues both with 5G experience and IT/OT knowhow across the board, which could be streamlined on every side to accelerate the sale and scale of new Industry 4.0 systems, he is actually moving the conversation along – into the realm of data science and AI.
And in so doing, he is taking a(nother) cheeky opportunity to plug Nokia’s own work, pointing to its proto-generative AI tool, MX Workmate, which goes with its edge network-and-compute products, and adapts large language model (LLM) technology, as found in consumer AI platforms, for OT environments. The point is to address the skilled labour shortage in Industry 4.0 – by filtering hard-won OT expertise via an AI chatbot trained on domain-specific data.
It’s a rascally ploy, in the context of a straight market review piece, but the point probably stands: one way or another, every party involved in the design and management of new Industry 4.0 systems has to ‘gen-up’ – on cellular systems, industrial systems, analytics systems.
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