From Asynchronous to Real-Time Communication: How Is the Process Industry Getting Prepared for the Next Level IoT?

Vivart Kapoor
September 16, 2019


Automation engineering specially in the process industry has always been a challenging area. The rapidly changing market environment demands higher productivity in the factories at lower (or ideally no) risks. Introduction of industrial internet of thing demonstrated how one can achieve higher productivity in a factory environment by collecting the sensor data and analyzing it in the cloud. This, in turn, gave birth to other productivity enhancement tools like predictive maintenance, asset monitoring, and tracking, digital twin and so on.

Even though the first results of the implemented factory IoT are quite promising, it is still only the tip of an iceberg. McKinsey article of digital manufacturing1 shows that the manufacturing industry produces more data than any other sector. Most of which goes unfortunately unused. It is not only due to lack of awareness but also due to the limitation of the current Operational Technology (OT) and Information Technology (IT) infrastructure. Two major issues the process industry facing at OT and IT level are:

  • Slow data transmission at sensor level: The commonly used field communication protocols at sensor level offers data rate (HART: 1.2 kbps, Profibus PA: 32.5 kbps FF: 1Mbps) which is not sufficient for high-end IoT application. The choice of using other non-bus powered Ethernet-based protocols is not available since they are not suited for Ex-Zone applications.
  • High latency and unmanaged data traffic: Quality high bitrate data transmission requires high bandwidth, low latency and quality of service. Moreover, in a complex system with several layers of critical, semi-critical and non-critical applications there is a need for an efficient data traffic handling. The commonly used industrial Ethernet-based protocols (Ethernet/IP, Profinet, MODBUS TCP) cannot handle this kind of complexity. These protocols do not offer priority scheduling of time-critical data.

Is There a Solution?

“Need is the mother of invention” –  If data is the key to good decision making then it must be abundant and need to move fast from the factory up to the cloud level. Fast and reliable data transmission is the prerequisite for machine learning and Artificial Intelligence (AI) implementations. Certain big player, societies and organizations came together to work upon new standards which can make OT, OT-IT and IT level fit for the mentioned task. These are briefly reviewed in the following.

OT Level: Advance Physical Layer (APL)

A joint initiative of various Fieldbus organization and IEEE, APL is protocol neutral, two-wire, a loop-powered physical layer for industrial ethernet which comes with a data transmission rate of 10 Mbit/s full-duplex. It offers a maximum trunk length of 1000m thus eliminating the need of repeaters in big plants.  The main feature of APL which makes it well suited for the process industry is that it will allow the powering of the sensor over the two-wire line (over APL field switches) which is specially designed for installation and operation in a hazardous area.

APL will overcome the shorting of existing sensor level Fieldbus protocols in terms of speed and compatibility. Introduction of APL will facilitate quick and efficient data transfer between the sensor and the PLC layer, with minimal hardware modification and retrofit stress.

OT to IT Level: Time Sensitive Network (TSN)

The need for low latency, high bandwidth and highly deterministic communication within complex system gave birth to TSN. TSN is a set of standards (fig.2) for the enhancement of current industrial Ethernet standard in terms of high speed (1 Gbps), low latency (few microseconds) and reliable communication.

Figure 1: TSN Sub standards (source:

Figure 1: TSN Sub standards (source:


TSN achieve these features by providing time synchronization to all devices and network switches which need to communicate in real-time. Moreover, the concept of the time-aware shaper (TAS) allows high priority (or time-critical) messages to be sent first.  The redundancy management feature of TSN allows the data packet replication in a network so that if the data get lost on the way, the redundant path still ensures its delivery to the destination.

Since the TSN is a base level technology (and not a standard protocol) which just like Ethernet resides at the data link layer of ISO-OSI model, it is fully compatible with other field-level communication protocols like Profinet, Ethernet/IP and OPC UA.

Figure 2: APL, TSN and OPC UA in the OSI model (Source: sps-magazine).

Figure 2: APL, TSN and OPC UA in the OSI model (Source: sps-magazine).


IT Level

Among the ongoing discussion of TSN compatibility with other high-end protocols, the combination OPC UA over TSN is something gaining the most popularity. Both TSN and OPC UA complement each other quite well. TSN providing fast and reliable communication at field level and OPC UA (with pub-sub extension) being the most spoken, secure and reliable protocol for the field to cloud communication.

Thanks to the idea of IIoT, the industry will soon witness the revolutionary developments in the field of factory automation which will turn the idea of real-time data transmission into reality. This is however just a beginning since there is more to come. Hopefully, the introduction of these new standards will bring the big (rival) organizations pushing their respective proprietary solutions to come together and work upon a common communication standard.



vivart kapoorVivart Kapoor is the Director of Industrial Internet of Things Solutions at Endress+Hauser in Germany. He is involved in the implementation of various IIoT projects along with business development activities. As a hobby blogger, he contributes regularly his expertise and knowledge in the field of the internet of things to several IoT expert panel or blogging sites. Vivart obtained his Bachelors in Biomedical Engineering from Manipal Institute of Technology in India and Masters in Technical Management from University of applied sciences in Emden, Germany.