In April, I was at Hannover Messe, one of the world’s largest trade fairs for industrial technology, which is held annually in Hannover, Germany. Due to COVID-19, the event was canceled for a few years, but this year, it was back, and, I’m happy to report, nearly at full scale. I had forgotten how massive it is. The sheer size of the event, with thousands of exhibitors and hundreds of thousands of visitors from all over the world attending each year, was truly mind-blowing. You need to have been there to understand.
The expo showcases the latest developments and innovations in automation, robotics, energy technologies, digitalization, and other related fields. The fair is withstanding the signs of time and is still a key platform for networking, business development, and the exchange of knowledge and ideas. Indeed, it remains one of the most important events in the industry.
One of the reasons that the fair withstands is probably due to the fact that it does evolve. In recent years, Hannover Messe has increasingly focused on the topic of Industry 4.0, which by now covers not only the Industrial IoT (IIoT), but also refers to the integration of advanced technologies such as AI and big data analytics into industrial processes. This reflects the ongoing trend toward digitalization and automation in the manufacturing sector and highlights the importance of innovation in the industry. Hence, my being there.
In fact, there are so many software companies now present at the fair that the whole event might succumb to its own success in adopting these new trends. At least that is what I felt when I spoke to a few engineers who were passing by our booth and were looking sad. I said: “Gentlemen, why so sad?” and while they looked at each other, one of them responded: “It seems that there is only software, but where are the tools? Where are the machines? Where is the smell of oil and grease?”
This remark highlighted for me a big transition that is occurring: Even the machine builders themselves now emphasize the digital side of the solution. No wonder, according to Gartner, 74% of the smart manufacturers now have an IoT strategy in place. (This is according to a quote I got from a Gartner analyst on the trade fair floor.)
Does that mean that everything is rosy now? No. There are still a lot of challenges ahead, especially for OEMs (original equipment manufacturers), and I spoke to quite a few of them at Hannover.
My take is that OEMs have a real struggle to get their IoT strategy properly in place. Why? There are a number of general reasons and some specific ones. Here are the general ones first: While the advantages of implementing IoT technology for them are relatively clear (helps to reduce unplanned downtime and ensure equipment reliability, which in turn, improves productivity), OEMs also face challenges when selling IoT-enabled products to their customers.
These include:
- Cost: The number-one thing they mention is always cost. Of course, by definition, IoT-enabled products are more expensive than non-IoT-enabled products, and their customers are hesitant to pay the additional cost, which is placing additional pressure on the margin of the OEM. The reason that customers are hesitant to pay the cost is often because the first value to be achieved is remote monitoring, something that is more to the benefit of the OEM than the customer. Only when the OEM can promise performance increases will the pressure on cost diminish, but that is an advanced use case that is not easily reached.
- Data security concerns: With IoT-enabled products, there is an increased risk of cyberattacks and data breaches. OEMs need to ensure that their products have robust security features to protect against these threats. This can be handled with a proper IoT architecture and using the right protocols. Hence, starting with a proven IoT platform, rather than a DIY from the ground up, has its advantages in this case.
- Supporting these new technologies is also a serious challenge for OEMs: To overcome these challenges, OEMs need to develop a robust support strategy that considers the unique requirements of IoT systems. This starts with building a strong support team. The team should sit beside experts, understanding the equipment itself consists of experts who are knowledgeable about the IoT system and can quickly diagnose and resolve issues as they arise.
But there is one particular challenge that is unique for OEMs: They are often just a small part in a bigger solution. Like the bearing supplier supplying bearings to a conveyor belt manufacturer (Can bearings be smart? Yes, they can), who is then delivering a smart conveyor belt to a mining company, who is building a smart mining operation. The conveyor belt manufacturer might be faced with dozens of IoT systems of their OEMs, and ditto for the mining operator. The conclusion? Integrating IoT systems between different equipment manufacturers can be challenging for OEMs because different manufacturers often use different communication protocols and data formats to transmit and receive data from their IoT systems. Additionally, there may be differences in the types of data that each system collects and how the data is processed, which can complicate integration efforts. To top that off, the systems might be on different IoT solutions running in different clouds.
To overcome these challenges, OEMs need not only to develop a comprehensive integration strategy that considers the different communication protocols, data formats, and data types used by their customers’ IoT systems, but they also need to decide if they should build their own solutions next to provide basic capabilities.
Some of the key considerations include the following:
Standardization: Developing and adhering to industry-standard communication protocols, data formats, and data models can help to simplify integration efforts between different IoT systems.
Interoperability: Ensuring that the IoT systems of different equipment manufacturers can communicate with each other and share data is critical for successful integration.
API development: Providing well-documented and user-friendly APIs can help to simplify integration efforts for customers and other equipment manufacturers.
Data management: Developing robust data management and analytics capabilities can help ensure that data from different IoT systems can be effectively integrated and processed.
Testing and validation: Testing and validating the integration between different IoT systems are essential to ensure that data is being transmitted and received correctly and that the integration is working as expected.
Overall, integrating IoT systems between different equipment manufacturers requires a thoughtful and strategic approach. By prioritizing standardization, interoperability, API development, data management, and testing and validation, OEMs can overcome these challenges and successfully integrate their IoT systems with those of their customers and other equipment manufacturers. In this way, they can evolve and reap the benefit of Industry 4.0, and, just like Hannover Messe, look ahead to a prosperous future. Just don’t succumb to your success.