Not too many years ago, one could still find a small number of IoT skeptics amongst fluid power professionals. Today, however, it’s become difficult for those last few IoT holdouts to substantiate their apprehension. There are the companies that have embraced IoT potential, and made it a core innovation initiative, and there are those that are at least monitoring their competition’s advances. Either way, from Hannover Fair to the hallway water cooler, IoT and digitization in general, are the talk of fluid power innovation.
What that looks like in practice varies from company to company. Some manufacturers are still focused on data collection, while others have moved full-scale into the realm of predictive maintenance capabilities and even augmented reality integration. So how do we collect data more efficiently? And more importantly, how do we use that data once we have collected it? Here, we’ve spoken with a couple experts to give us a look at what fluid power IoT looks like at the ground level.
Data at the forefront
To start at the beginning, the core of any IoT solution is the hardware of the telematics devices actually making the connections for information transfer possible. That could be WiFi connecting to a local network or cellular or satellites connecting to the Cloud, the server, or some other storage location. “That has applications for the whole lifecycle of the machine, from initial design concept on through to production and field service,” said Joe Maher, Product Marketing Manager-Electronic Components for Danfoss Power Solutions.
“But how do you get that data? How do you start making it valuable? That’s what it’s all about. The system is accumulating large sums of data. If I have been accumulating data on several components or machines in different applications in all regions of the world, and I have multiple instances where I can show in the data that I’ve had a component failure, imagine that at that point I look at all of the data behind it and I start detecting patterns. What can I do with that? If I see a typical pattern that repeats itself before these component failures, now maybe I can take that pattern and project it forward. Now maybe I can forecast when one of those failures is going to happen. How much would that be worth?”
This need for data acquisition and pattern recognition has created a call for specialized talent in the work force. Enter the data scientist. This is certainly not a new title or position—just ask the HR managers at companies like Facebook or Amazon. But the need for their skills in the fluid power space is just now being pushed to the forefront.
The data scientist’s job, of course, goes hand in hand with a company’s other team members dealing with physical infrastructure. Both must work together to secure data and ensure that it’s not corrupted. Privacy is also a primary concern. Contractual obligations with customers abound and the industry trend has also manifested itself in terms of communication protocols.
There are standard communication protocols for this type of data—such that you can have information coming from multiple components, multiple brands, but all collected in the same spot so that you can aggregate all the information and analyze it. It’s at least possible that fluid power customers could eventually have a machine dashboard that gives them information about the health of their different systems and perhaps even a recommendation on action plans if components reach a suboptimal level. These are just a couple of examples. There are many other potential uses for a machine dashboard like this.
For example, with GPS, if we have a device on a fleet of machines, we can tell where all those machines are. A rental company is an obvious example. For the owner of a fleet or a job site foreman with a number of machines in operation, now they can see where all their machines are at all times. No longer does it require that they make multiple phone calls to figure out where they are, and all the subsequent logistics.
Maher takes it a step further.
“So now that I can tell where all those machines are, what if I could put a virtual fence around some geographic location? What would I do with that? Well, for example, if I’m a rental company and the contract stipulates that the machine that I’m renting will be operated in a certain area, with a different rate if you go outside of that … well, that would have some use for me. Maybe I can have my machine programmed or my information portal programmed so that whenever a machine goes out of that area, I get a note, a text message, an email, that can all be automated. In fact, at our development center in Ames, Iowa, we have this around our garage. The manager of the development center knows whenever a machine is leaving the garage.”
Giving machines a voice
The IoT integration platforms of companies go by many different names. At Parker, they call it Voice of the Machine. This is the phrase Parker uses to classify its digital transformation initiative and it’s a good example of what we can expect from IoT in the fluid power industry down the line. This approach to IoT includes their centralized initiative to standardize IoT technology across their businesses, IoT-empowered products that result from that initiative, and their focus on customer needs. Voice of the Machine establishes a common set of standards, principles and best practices across Parker’s operating groups. As a result, all of the company’s products use the same communication standards, security architecture, and visualize data in the same way. This helps to ensure interoperability and a consistent user experience.
From a technology perspective, Parker says it has focused its efforts on minimizing the challenges that have prevented operators in critical industries from using IoT to solve operating problems, such as downtime and maintenance costs. For engineers who have considered greater IoT integration, challenges like legacy devices that are not IoT-enabled, competing communication protocols used by various suppliers, securing devices and data, and determining what data to collect and how to present it, are certainly familiar. Jeff Smith, Business Development Manager–IoT at Parker, said simplification of IoT integration is central to their business model.
“As you may know about Parker, we make many discreet things and many different parts. Voice of the Machine is really the umbrella for Parker, around our IoT initiative, and so as we start to empower these discreet elements so there is one simple platform that we use for people to see their data, run reports and get alerts. It’s important for us to have a center initiative so that anybody buying Parker related products, if it was IoT empowered, they only had one software platform to come to,” Smith said. “This really is the main idea behind Voice of the Machine. We have built out these elements of the platform where any of these divisions can really consume that platform.”
Specifically, at the component level, for example, there is the ability to have an interface to log into for data on a pump. This provides some kind of an overview where a user can get flow rates, temperature, pressure, and discharge pressure, among other data sets.
In another example, let’s say a user has a fleet of pumps in multiple remote locations requiring long drives between sites. Being able to access a centralized dashboard would be quite valuable. Smith continued, “If we can communicate with any location, we can also command and control it—from turning it on and off to changing the speed of the drive or modifying the flow rate. Much like a volume knob, we can turn that up or turn that down remotely. We don’t have to be there.”
Additionally, all of these kinds of things are tools a user can log and track. This gives people different access options. If one person is on site, they only have access to things on their site. Or if somebody is a fleet manager, for example, they can see that fleet. This is all in an effort to help improve the continuous operation of these pumps over time. Shrinking the space between geographically separated components, the ones measured in miles as well as meters, is important to the future of IoT. It’s that level of real world application that’s helping bridge the gap between theoretical value and actual business advantage.