Hannover Messe 2022: Summary and Key Takeaways

Hannover Messe is back after a multi-year pandemic-related hiatus. Historical attendance was in the vicinity of 6,500 exhibitors and 250,000 visitors, which is about double the major consumer shows like CES at their peak. This year was understandably different; the Messe date was pushed from April to the end of May/start of June during a period when different regions, including the United States and the United Kingdom had national holidays. Initial estimates put 2022 participation in the vicinity of 2,500 exhibitors and 100,000 attendees (~40% of past participation).

ABI Research had a small army of analysts on-site to cover a range of topics and share the latest. Standout areas worth mentioning include 5G, AM, AI, automation, DTs, edge, sustainability, and vertical markets. Others are industrial cloud, SaaS, servitization (XaaS), simulation, and security.

AI: There were many undertones of AI, from optimizing edge/cloud workloads to High-Performance Computing (HPC) for simulation and generative engineering applications. One applied scenario demonstrated by software provider Senseye is using its anomaly detection more broadly for investigative scenarios beyond predictive maintenance. The company’s algorithms and customer value experiences are now refined to the point where it offers “ROI Lock,” which essentially means that the customer gets a full refund at the end of the year if the solution did not generate the intended Return on Investment (ROI). This aspect of the solution is insurance-backed and validated by the fact that Senseye has not had to return any business up to this point.

This insurance-backed guarantee is one potential onramp to servitization (XaaS business models), as demonstrated by Relayr. Another is to use these data for a physical-first product, as industrial bearing provider SKF has done through its partnership with Amazon Web Services (AWS) for a retrofit sensor. Eventually, SKF will sell rotation and motion, rather than actual bearings.

Edge: Edge is of growing importance for several reasons that include, but not limited to low-latency industrial automation and control, Time-Sensitive Networking (TSN) applications (e.g., robotics or collaborative robots), security and data ownership, and data workload optimization. With respect to the last aspect (data workloads), there are new and upcoming solutions that will allow an engineer or operator to run an optimization on a virtual simulation of a work cell, production line, or plant. There is a range of scenarios where this capability might be needed, but one example is if you need to meet production targets, but inputs change (e.g., a machine breaks, personnel do not show up to work, or supplier issues arise).

Digital Twins: Nearly ever booth displayed a component of a DT, from design and engineering through manufacturing production and after-sales service and support. ABI Research covers this market extensively through our syndicated research, including reports like Industrial Digital Twins: What’s New and What’s Next (AN-5478). The most comprehensive example at the show was at the Siemens booth.

Siemens is far ahead in the world of DTs, in part due to its heavyweight title in industrial automation and control (hardware), and very much in part due to the longstanding, but recently accelerated investment in industrial software. By comparison, companies like PTC, Ansys, AVEVA (Schneider Electric), and Rockwell Automation—all of which have a role to play in standing up a digital twin offering—did not have a dedicated booth; instead, they were co-located with hyperscalers (Microsoft Azure, in this case).

Two relevant observations regarding DTs: 1) Many IT-centric providers have failed to translate and stratify their infrastructure-focused concepts to the world of Operational Technology (OT). Examples include Red Hat and Hewlett Packard Enterprise (HPE), although the latter has more of a near-term opportunity to be an exception to the rule through concepts like edge networking and integration; and 2) many OT-centric providers are growing under the wing of larger partners, including AWS (especially), Microsoft (also), and Google Cloud Platform (GCP) (to a lesser extent). SAP and Cisco were two other booths that had extensive partner displays.

Upcoming innovations to be aware of for DTs include the application of Executable Digital Twins (XDTs), the optimization of edge/cloud workloads to maintain digital twin models, marketplaces to speed time to market/value, and a better delineation and definition of the metaverse.

Sustainability: One of the most universally prevalent themes, sustainability represents an attractive, unpriced negative externality. Negative externalities occur when one activity is harmful to the agent of another. Traffic congestion, noise pollution, and a bystander inhaling smoke from an active smoker are a few general examples of negative externalities. In manufacturing, Carbon Dioxide (CO2) emissions are one of the most common examples of a negative externality, because we’ve yet to capture the cost of environmental pollution and translate that cost into something contributors pay—at least not yet at a meaningful scale.

In some ways, sustainability is much like 5G now and especially a few years ago. ABI Research noticed a fair share of booths with large amounts of sustainability text or suggestive images that currently manifest as nothing other than a new moniker. When asked what is new, the most common response was “yes, it is important; yes we are thinking about it; maybe we have some vague general plans or at least a VP; but no, we haven’t really done much. This last part will be the biggest change when it comes to sustainability in the next 2 years, as many companies work to improve transparency and accountability throughout the production chain.

5G: Automotive was regarded as an early leader in private cellular deployments due to the large footprint, high degree of automation, and overall complexity of operations, but many of these instances still need to graduate from Proof of Concept (PoC) or Research and Development (R&D)-type projects (the lack of available 5G devices is a near-term headwind). Contrary to early wins/pilots, there has also been a recent uptick in 5G in process industries, which is detailed in ABI Research’s vertical market reports, in addition to the Digital Factory Data market data (MD-IICT-107), which tracks the factories that have deployed private wireless. It will be several years before we see 5G in manufacturing production at a meaningful scale.

Additive Manufacturing: AM was greatly muted as a theme compared to years’ past and what we expect to see at IMTS in Chicago in September. Part of the reason is likely the delay of Hannover Messe, such that it was only a few weeks after RAPID, one of the largest AM events in the industry, held annually in Detroit (the other is Formnext, held in Frankfurt in November).

In terms of booth presence and conspicuous absences, Markforged and Formlabs had the largest AM booths to the naked eye. Stratasys was co-located with a European reseller partner and also had a notable presence. Markforged and Formlabs are a different tier from 3D Systems, HP, and Stratasys when it comes to the ability to support industrial production applications, although segments of their respective portfolios are considered competitive. Rather than issue a bunch of new announcements at Hannover Messe, the strategy seemed more to support and amplify initiatives announced at previous RAPID and Formnext events. Inconspicuous absences included EOS, Desktop Metal/ExOne, HP, and 3D Systems, to name a few.

Next-Gen Industrial Automation: A handful of cloud-based Manufacturing Execution System (MES) providers, such as PLEX (acquired by Rockwell) and 42Q (a subsidiary of Sanmina) are working to bring the same Industry 4.0 automation from Ford, GM, and Tesla to SMEs. One of the biggest challenges addressing these markets is the fragmented approach to industrial automation, most of which stems from the fact that, often, multiple different plants producing the exact same product could be using completely different equipment. This makes standardizing on key learnings and innovation not only difficult, but nearly impossible. It also makes it very difficult to drive innovation from the top down.