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Impact of IIoT on automation systems design

28 May 2015  | Suhel Dhanani

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But that is not all. The IIoT promises that this data can be integrated within the manufacturer's ERP and CRM software. The manufacturing operation will be able not only to plan and cost out manufacturing processes more efficiently, but even to use customer information to change assembly lines and process parameters in real time.

The bottom two stacks in figure 2 impact the design of your system hardware, and the top layers affect your software development and integration.

The critical role of sensors in the IIoT
The IIoT is not a mere buzzword. Factories have started using a large number of connected sensors and, by linking them to powerful computers, have begun to create the backbone of the next-generation "smart" factories. Once all of the industrial data (i.e., the "things," the "T") is finally interconnected online (i.e., the "Internet," the "I"), then complex software can be used to optimise just about anything.

A good place to find an actual IIoT is at GE's newest U.S. factory,5 a $170 million plant opened in upstate New York about a year ago. It produces advanced sodium-nickel batteries for applications that include powering cell-phone towers. The factory has more than 10,000 sensors spread across 180,000 square feet of manufacturing space; all sensors are connected to a high-speed internal Ethernet. The sensors monitor processes that determine which batches of powder are being used to form the ceramics at the heart of the batteries? How high is the temperature being used to bake them? How much energy is required to make each battery? And even what is the local air pressure? Employees with iPad computers on the plant floor can pull up all the data from Wi-Fi nodes set up around the factory.

Airbus, headquartered in Toulouse, France, also announced that it has come quite far in applying the IIoT to create their Airbus Factory of the Future.6 At a recent NI week presentation,7 Airbus showcased how they have attached RFID tags to objects such as aircraft components and tools. These tags can then be read automatically from distances of up to 100m using special glasses (similar to a Google Glass™ head-mounted display8) through which Airbus can track and visualise production processes in real time. According to Airbus, this visualisation technology has been deployed on the A330 and A350 final assembly lines in Toulouse, France, and on the A400M wing assembly operations in the U.K.

While, for now, it seems that the Airbus project is limited to digital tracking and monitoring using RFID to increase industrial operations efficiency, their concept can be extended to other types of analysis as well.

The promise of the IIoT
We need to be very clear about why everyone wants to make the IIoT viable. The overriding answer is systems optimisation, and all the benefits that optimisation usually brings. These benefits can be broken down into three primary buckets: asset, process, and business optimisation...each addressed in that order. It is easier to optimise a motor than to optimise a whole drilling operation which, in turn, is easier to optimise than the many manufacturing lines of a large enterprise.

But optimising all of these is the essential dream of Industrial IoT (figure 3).

Figure 3: Benefits of the IIoT. All the factory/process data is online (cloud), so software analysis can help with asset optimisation, then process optimisation, and eventually business optimisation.

Asset optimisation
The first level of analysis and interaction occurs at the edge. The data is collected from a sensor, perhaps a wind turbine sensor, or a motor encoder, or the vibration signature. This data is processed locally to help operators understand how to adjust parameters for the highest efficiency or for an early indication of a potential failure.

Process optimisation
The next level of analysis happens at the control room. Here sensor data from multiple end devices and even multiple assembly lines is aggregated to enable more intelligent decisions that could positively impact factory efficiency and multiple processes. For example, with more accurate sensor data a control room can make smarter decisions about when end devices should be idle or asleep. One positive benefit will be better hardware usage and, probably, a reduced power profile.

Business optimisation
There is a common denominator evolving from this discussion: more data and smart data usage. We are all familiar with how data can positively impact asset usage and process operations. But the IIoT envisions not just an increase in data collection and analysis at the first two stages. The IIoT also promises to integrate the process data with the enterprise data and thus enable really interesting, smarter management decisions that, so far, have not been made.

Consider, for example, an assembly line that can now be programmed to manufacture higher volumes of a product enjoying a market explosion, or programmed to bypass sub-assemblies with diminishing market value. Even a combination of operating and financial data might be used to provide more insight to the CFO office.

The IIoT is still in its infancy and has no dominant platform standard. This is the "wild-west"9 phase of the IIoT and is precisely the right time to develop and drive acceptance of a platform standard. And that is exactly what we see automation companies doing.

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