With new connected products and solutions emerging every day, the Internet of Things (IoT) and its Industrial counterpart (IIoT) are thoroughly in the mainstream. In a recent survey from ENGINEERING.com, over 60 percent of product development professionals responded that they’re adding or evaluating adding IoT capabilities to their products.
But the IoT isn’t quite as simple as sticking a Bluetooth chip into your design and calling it a day. Rather, the IoT is a tool that can be used to enable many useful features—features like device management, performance analytics, asset tracking, predictive maintenance, energy optimization,control optimization, and more. If you’re a product designer, it’s important to understand which of these features to enable with your IoT solutions.
In the aforementioned survey, IoT Features in New Product Development, we asked product teams which of the above features they were including in their IoT designs. The results may surprise you: for all intents and purposes, these features are adopted in more or less equal proportion. In other words, if you’re enabling one of them, you’re enabling all of them.
To help interpret these results, we spoke with Jagannath Rao, Head of Data Driven Services at Siemens and director of their cloud-based IoT platform, MindSphere. He spoke about some of the ways that Siemens customers are using these particular IoT features, and ultimately provided some insight into the survey results.
The Packaging Industry
“These are all important and useful use cases,” says Rao,commenting on the six IoT capabilities shown above: automated device management, analytics of product performance, asset tracking in the field, predictive maintenance, energy and use optimization, and control loop performance optimization. MindSphere, Rao explains, is geared towards all of them.
“We want the whole idea of having the ecosystem on top, opening it up to anybody who wants to develop applications and services,” he says. “The idea is that many different use cases for many different industries come onto the platform.”
To illustrate his point, Rao gives an example from the consumer packaging goods industry—specifically, a bottling plant. These types of plants are typically driven by a few hundred small motors, each of which costs only about two hundred dollars or less. Because of the low cost of replacement, these motors are often driven to failure and simply swapped out.
“The problem with this is you have unplanned downtime and you could have wastage, so there are all these hidden costs and productivity issues that happen,” Rao explains. The solution? The IoT, of course.
“In the process of connecting these plants to an IoT platform, we're able to introduce what is labeled in the marketplace today as cost-effective wireless sensors,” says Rao.“These are sensors that are sold for just ten bucks, and they wirelessly transmit data on vibration and temperature, for example.These sensors have a little sticky tape on the bottom, and you just stick it on the motor and it starts transmitting data.”
Right away we can see how this example touches upon automated device management—these sensors must be capable of sending their information to an IoT platform.
“Primarily what is important there is the ability to automatically transmit data when you get connected to an IoT platform, and that is something that is already configured right from connectivity into that device,” says Rao. “The other aspect of device management is the ability to configure or troubleshoot or upgrade these devices and manage them remotely.”
Back to the bottling plant:
“So we would put the sensors on the motors. MindSphere collects this data, and then the platform manages this fleet of motors, constantly monitoring the data,” Rao explains.“When the data goes into some sort of abnormal range of temperature and/or vibration, then it is known to the staff of the plant that something is going to happen. So, therefore they're able to replace these motors in a planned shutdown.”
Now we see another IoT feature come to light: predictive maintenance. Using the data collected from their motors,the plant staff can take pre-emptive action when a motor is near failure. It’s also clear how the motor manufacturer might add IoT-enabled performance analytics into their motors: if temperature and vibration sensors were built into the motor, we could skip the stick-on sensors entirely.
Machine Tool Management
Rao gives another example that lends itself to many IoT-enabled features: machine tools.
“We also have an application on our platform now which is called ManageMyMachines, which is specific to machine tools,” he says. “Machine tools are classically in the OEM [Original Equipment Manufacturer] arena, and largely used in the automotive or aerospace industry and many other applications.”
OEMs often have many different machine tools, sometimes spread out in facilities around the world, and would love to be able to monitor and manage their entire fleet.This would allow them to look for data anomalies, understand the performance of their assets, and help in planning and scheduling maintenance.
“OEM’s now are able to connect all their machine tools on the MindSphere platform, and start monitoring all aspects of their machine tools,” says Rao.“They can get predictive data on what might go wrong with the machine, which gives them enough time to schedule maintenance. They know which part of the machine is showing troublesome behavior., and they know what kind of inventories they need to keep.”
Predictive maintenance is only one advantage of monitoring an entire fleet of machine tools. The data collected from all these assets can be used help optimize an OEM’s entire operation, from energy use to cycle times of operations to the performance of individual machines.
“By collecting data from thousands of machines, OEMs can start some kind of benchmarking,” Rao explains.“That leads to programs that they can build to optimize their operations. So there's a whole lot of things that machine tool OEMsare doing now, just connecting via MindSphere and using applications like ManageMyMachines which is provided on that.”
Automatic First Applications
Perhaps now the survey results we saw earlier will be less surprising. Rather than the IoT presenting a single killer feature to kick off adoption, the IoT enables many killer features, each of which are easily tied together. The most important parts of the IoT are connection and collection: if you can collect data from a device and share that data over a wired or wireless connection, you’ve opened the door to a whole host of IoT features.
“Everything that's listed here [in the survey report] is an automatic first application for most customers,” says Rao.“Think about predictive maintenance. That's a classic arena—everybody wants to be able to do analytics and predictions and look at problems in machines and build a maintenance program around that. Asset tracking is the same thing, and so is energy use and optimization. When you're connected to the platform you're able to get all energy consumption data from many different data sources, and you're able to do energy analytics and start optimizing usage. So I think almost all of these are one of the first use cases that come to most customer’s minds. And I think that's the reason this has come out in your research pretty clearly.”
For product designers looking to add IoT capabilities to their designs, the results may be a bit of a mixed bag. On the one hand, there’s no single IoT-enabled feature to point at as the killer capability, the one you simply must include in your product design. But on the other hand, it’s clear that the IoT is a very versatile tool—if you can make your product connected and get your data collected, you’re well on your way to IoT success.
To read the research report discussed in this article, click here.
Siemens PLM has sponsored this post. They have no editorial input to this post. Unless otherwise stated, all opinions are mine. —Michael Alba