The impact of IIoT on industrial communications

29 September 2017

Industry 4.0/IIoT and the new communication technologies coming to market are providing the foundations for the next industrial revolution, says Susanne Cumberland.

The modern industrial market is intensely competitive and smart manufacturing in factories allows more than just basic functionality. The networking of devices, machines, and humans on the factory floor has been at the forefront of industrial automation. Connectivity is not new; as mobile devices, PCs, tablets, and other similar devices in use have allowed the collection of large amounts of data. The idea of large-scale connectivity has now moved into the world of industrial automation, through IIoT/Industry 4.0 concepts.

Intelligent devices and machines create a large amount of data that can provide much new detail on processing and management on the factory floor. With such large quantities of data, there is an increasing need for analytics to create the insights that can improve productivity, efficiency, and ultimately profitability. The use of embedded sensors has begun to influence ‘basic’ components used in industrial automation. 

An example is valves, where sensors detect the status of the valve through monitoring select parameters, such as vibration. By networking smart valves, data can be extracted and analysed to provide valuable information for various aspects of a business; such as predictive maintenance. Wireless acoustic transmitters have been used with steam traps for monitoring. A failure can result in high-pressure steam leaks or an accumulation of water that moves through the pipes and equipment. The latter can rupture steam lines and cause turbine problems, resulting in expensive repairs and significant downtime. 

IIoT is helping companies to shift from preventive to predictive maintenance. Predictive maintenance is the direct monitoring of a machine to relay information on its status, and predict a potential failure. Its application can help a company reduce unplanned downtime, reduce equipment repair costs, and reduce labour through more efficient use of maintenance teams.
IIoT cannot happen without connectivity, and this increasing demand for the networking of devices has boosted the shift from fieldbus to Ethernet networking. However, the cost and inconvenience of a ‘rip and replace’ of the network has limited Ethernet growth, some factories are having parallel installations deployed so their production lines can evolve. However, some industries like automotive are moving more quickly to Ethernet. The growing demand for electric cars is having an impact on Ethernet networking. Electric cars have different production requirements to a combustion-engine car meaning a factory rebuild is a must; this is an opportunity to use Ethernet networking instead of fieldbus.

Within IIoT, awareness of OPC UA is expected to increase and will grow significantly over the next few years. OPC UA provides an open and dependable mechanism, with the additional benefit of improved security in transmitting data outside of the factory.  It is often seen as a complementary technology in industrial automation because of its interoperability. It can be an additional layer that allows vendors to provide machine-to-machine communication without having to create their own, as it will work over Ethernet. Some automation vendors are already introducing it into their higher end PLCs and IPCs – with a number of other vendors also indicating planned releases for 2018. 

The implementation of OPC UA is predicted to extend to more basic control products as well as other technologies such as servo drives and variable speed drives. The OPC Foundation has had several developments in 2017 that will include OPC UA.Net standard stack, memorandums of understanding in robotics, and a publication of an international standard MCS DCS interface in the oil and gas industry; as well as the release of the OPC UA Pub/Sub definition, due out late 2017/2018. These developments expand the product portfolio that OPC UA will serve.

Another important development is TSN. Time-Sensitive Networking (TSN) enables deterministic real-time communication. TSN reduces deterministic transfer times and time synchronisation between nodes, allowing fast response times. This ability to transfer and share time-sensitive data is an important aspect for some industrial automation sectors, such as robotics, where a delay in data can cause production problems. TSN-enabled products are planned to be introduced for industrial automation in late 2017/early 2018. This enablement requires the addition of a dedicated chip on the device. This hardware change (as opposed to merely a software update as is possible for OPC UA enablement) means the rate of release of enabled products will be protracted and TSN is not forecast to be a broadly installed technology in automation within the next five years. Any form of plug-and-play solutions, which is possible for Industrial PCs and some PLCs, will increase the adoption of TSN; without such a solution, a retrofit is required, an expensive alternative that would hinder its adoption.

To remain competitive in industrial automation, vendors need to provide more than functionality; Industry 4.0/IIoT is a concept that makes use of connectivity and data collection to offer improved efficiency, productivity, and profitability. One example of how data collection can benefit industrial automation is predictive maintenance on valves for steam traps, which can increase efficiency, reduce repair costs, and reduce downtime. 

The increasing demand for connectivity and intelligent devices is speeding industry’s move from Fieldbus to Ethernet networking and driving high growth rates for OPC UA.  The growth of OPC UA has been boosted by the fact it is open, interoperable, and has improved security. Additionally, it is a software change that is easy to implement, unlike TSN. TSN requires a dedicated chip on the device, which means that unless there is a plug-and-play solution available, retrofitting is required. 

Susanne Cumberland is research analyst, Discrete Machine-Safety at IHS Markit Technology.

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