As computers get smaller and more powerful, engineers have begun exploring the potential of placing computers at the edge of networks, closer to the machinery and equipment being monitored and managed. The theory is that additional computing and data processing at the edge will simplify the integration of industrial equipment data into an Internet of Things (IoT) database.
This approach offers many benefits for the majority of industrial users who are not in a position to replace existing equipment. However, successful execution requires an understanding of the core issues at play. For starters, there are three key integration complexities to address:
- Differences between fieldbus protocols and IT protocols. The world of computers, IT protocols and databases are all designed around data manipulation and management, and are highly integrated with each other. Fieldbus protocols and the machinery that run on them have completely different purposes and requirements. For a database engineer accustomed to data produced by typical computer applications, it requires a great deal of effort and study to bring data from Modbus, EtherNet/IP and Profinet devices into a common database.
- Differences between programming languages. The most common programming languages for computer platforms are C/C++, Python, Java, .Net, etc., all of which offer a rich set of tools, software and application programming interfaces to support various database applications and platforms. These programming languages, however, do not have any tools or support for industrial protocols. For the industrial space, IEC 61131-3 is the most common programming language and offers deep integration with industrial protocols. However, IEC 61131-3 is not designed to integrate with the database platforms used by IT networks and systems.
- Familiarity with networking technologies used in the IoT and its application in Industrial IoT (IIoT). Most engineers and users are fairly familiar with the networking technologies leveraged in commercial IoT applications, especially wireless. However, the adoption of certain networking and wireless technologies has been limited in the industrial world, partly due to the common perception that wireless networks are inherently unstable.
Even when faced with a highly complex integration effort, manufacturers, engineers and users still see vast potential benefits in the IoT and are looking for ways to resolve complexity. Edge computing has been touted as one of the solutions, but the challenges above need to be addressed first. We believe that a number of developments have made edge computing a much more attractive and compelling option today than it was just a few years ago. The two most important are:
- Most industrial fieldbus protocols have developed into standard Ethernet-based protocols. A decade ago, it was a given that equipment communication would be over proprietary, closed fieldbus protocols that required special hardware. Industrial Ethernet has completely changed the landscape, and almost all the modern popular fieldbus protocols are now standard Ethernet-based. That means a computer platform can easily use its Ethernet interface to communicate with most of today’s industrial equipment.
- There are many communication equipment providers now catering to the industrial user for communication over different types of media. Edge computing can be used to restructure and store the raw device data into a database-friendly format, and the other pieces of equipment can be used to collect and/or transmit the data as needed.
There is going to be a growing demand for flexible and easy-to-use solutions that are tailor-made for industrial users, rather than commercial products bolted onto industrial equipment. This is one reason we started combining multiple device functions, including 4G LTE connectivity and industrial protocol support, into our edge computing products. This makes it possible for IT engineers to work with the IT programming language and databases that they are most comfortable with to access industrial data, instead of forcing them to work with multiple devices and develop their own protocol conversion algorithm. It also reduces the overhead for system integrators and users that are trying to read the industrial protocol data and place it to a computer database.
The illustration accompanying this article shows some of the tools that can be provided on an edge computer to further reduce the complexity of integration for an IIoT system. The idea is to allow engineers to focus their efforts on data analysis and developing applications on the edge computer, instead of also having to develop or acquire additional solutions for 4G connectivity, fieldbus communication, VPN or system diagnosis. The easier you can make it for application developers, the more easily they will be able to deliver the valuable real-time insights that IIoT makes possible.