The Industrial Internet of Things (IIoT) market is in the early stages of a growth curve comparable to the evolution of the mobile telephony, especially when it comes to IIoT vibration sensors. In this scenario, is the current business model of keeping systems closed compatible with the future of IIoT? We believe sensor expansion will inevitably lead us to more open ecosystems.
In 2022, the number of IIoT vibration sensors sold will reach a couple of million devices per year. While this may sound impressive, in around 10 years, we expect it to grow to some billion sensors sold annually. Yes, with a b.
This massive growth can be explained when we look at the state of machine monitoring in the world. In developed economies, condition monitoring has only been done on critical machines, which is about 10% to 20% of equipment . Meanwhile, the remaining 60% to 70% of machines that are still essential have never been monitored before.
And when we look at emerging economies, the percentage of monitored assets is even lower than 5%. There’s a wide gap in both critical and essential equipment that have yet to be monitored, mostly due to the costs involved in setting up a traditional condition monitoring system.
We are now where mobile phones were three decades back: a promising technology, with limited availability, that is gaining traction as hardware advances. The end of this story is known to all, as 1,5 billion cellphones are sold annually. Vibration sensors are reaching, for the first time in history, a price point that enables its use for several million and maybe even billions of machines. We have the opportunity to not just cover critical machines but also the essential ones.
But the current scenario is still one with closed ecosystems. A company that wants to perform 24/7 remote monitoring of a machine has two options: purchase a new equipment that already comes with embedded sensors from an OEM and acquire their data storage and analytics services or buy wireless sensors and also be tied to the vendor’s services of storage and analytics.
As P. Zhang, H. Zhu, and Y. Wu describe in their paper , “existing IIoT is always developed by a single designer or company, whose core technology and data are inaccessible to other individuals. This type of IIoT operates in a close and rigid manner, with limited scale and functions. Users have few accesses to IIoT data and programs, which largely restricts the applications of IIoT under various user requirements and operation environment. With increasing complexity of power system and industry, traditional IIoT fails the demands for flexible and efficient system monitoring and maintenance.”
T here is a traditional practice of closing ecosystems, and naturally OEMs had their own reasons for doing it , because they used to provide very expensive hardware and software for monitoring. Today, we estimate that 95% of vibration sensors available operate in closed ecosystems.
The disadvantage is that the moment you want to do widespread adoption and scaling from a few to several million machines , it becomes impossible. Another downside is becoming tied to a single provider, without any flexibility in terms of usability and technology.
But as wireless (and even wired) vibration sensors reach a lower price point, almost everyone will have access to decent-quality hardware. The other elements of the ecosystem, like data storage and transmission, are also becoming more accessible. We forecast that by 2035, the majority of the sensor market will be open hardware companies, leading to greater freedom of combining condition monitoring hardware and software.
One of the signs that point to this direction is that maintenance companies are introducing their own vibration sensors in the market, in a bid to compete for costumers being targeted by the aftermarket efforts of OEMs, as we wrote in an earlier post . An open ecosystem gives them flexibility to create their own offer, at a reasonable price, and the chance to stand up to OEMs’ closed ecosystems.
We, at Viking Analytics, have chosen to contribute to the use of open hardware that can interact with any software systems. We developed MultiViz Vibration with the aim to enable any vibration analyst, any maintenance provider, and even OEMs to provide vibration based predictive maintenance by making use of all these open vibration hardware, flexible cloud or on-premise data handling options.
By enhancing the knowledge of vibration analysts and letting they do their work in a more efficient way, they can provide AI condition monitoring and vibration predictive maintenance solutions without needing to hire an army of data scientists, and without having to depend on closed structures imposed by OEMs.