Stimulus for New Automation Architecture

February 062015
Stimulus for New Automation Architecture

Bill Lydon’s Automation Perspective

By Bill Lydon, Editor

I believe the growth and application of new technology is a stimulus for the development of new automation system solutions and architectures. These new technologies include, but are not limited to, the Internet of Things (IoT), big data and cloud analytics.

The industrial automation industry has experienced relatively few changes over the years. I believe the following developments are the major milestones in the evolution of automation:

Programmable Logic Controller (PLC) – In the 1960s, the PLC was developed as a programmable device to replace relay control logic in machines and assembly processes. Particularly, in the automotive industry, large cabinets of relays, cam timers, and drum sequencers were configured to control production devices such as motors, solenoids, and valves. These devices consumed a great deal of power and physical space. Logic changes required extensive planning, engineering, and wiring changes, all of which were expensive and prone to errors. Complicating this further, coil failures and contact wear were difficult to diagnose and replace. Rather than hard wiring these devices, PLCs were programmed to control the system and logic changes were dramatically simplified. The PLCs were programmed using Ladder Logic, which consisted of symbols that looked like relay contacts, coils, and timers. By organizing these symbols in ladder rungs, the application engineer created a control logic sequence. This method of programming greatly simplified the process for engineers and technicians because they understood how to design control systems with these components.

Distributed Control System (DCS) – In the 1970s, DCSs were developed for process control applications. Control elements are distributed throughout the system using microprocessor technology. In that timeframe, Direct Digital Control emerged for process loop control using computers or microprocessors rather than pneumatic or electronic analog controllers.

Open Networks – Starting in the late 1970s, standard open network communication protocols were established for industrial communications. Modbus was the first. Control systems evolved to provide coordinated control which required networking of control processors. Initially vendors developed and supplied their own proprietary, closed protocols. Today, Ethernet has become the industrial network backbone for open industrial protocols. Generally, DCSs use Ethernet hardware and transport mechanisms, but they still have proprietary control network protocols.

Open Programming – Each vendor had their own proprietary programming methods until the establishment of the IEC 61131-3 standard, which was first published in December 1993. Vendors conform to different function as noted on the PLCopen website.


The scope of the Internet of Things (IoT) is very broad and includes a wide range of applications, such as personal health, energy metering, entertainment, security, and transportation. The concept of IoT is the networking of all physical objects, each equipped with embedded sensing and/or communication ability, to improve efficiency and productivity. The development of technology for high volume IoT applications is already making available sophisticated low cost building blocks that can be applied to industrial automation.

For example, Intel CEO Brian Krzanich plucked a button off his blazer during a keynote speech at the 2015 International Consumer Electronics Show in Las Vegas, Nevada, and explained that it contained a System on a Chip (SoC) computer, called Curie. Intel’s Curie device includes 384kB flash memory, 80kB SRAM, Bluetooth radio, 6-axis combo sensor with accelerometer and gyroscope, and components designed to rapidly and precisely differentiate between different types of physical activity. In the past, commercial computer and electronics developments were used as elements to build industrial automation systems. Today these building blocks can be used to develop programmable industrial automation edge devices.

Intel Curie System on Chip

If you think this is a stretch, I know some experienced automation people that are using Raspberry PI single board computers. These wired and wireless Ethernet computers are monitoring and logging historical information from field sensors, and also communicating with automation systems, historians, and enterprise business systems. You can buy a Raspberry PI starter kit on Amazon for about $70.

Cloud Analytics

Cloud services are rapidly being developed for IoT applications that can be directly applied to industrial automation applications. Both Google and Microsoft have cloud applications for users to store historic data and perform analytics on a pay-for-use model. The Google Analytics Measurement Protocol allows developers to make HTTP requests and send raw data directly to Google Analytics servers, store it and use the rich set of Google analytics to analyze it. The Microsoft Azure Machine Learning is more refined and offers the ML Studio integrated, drag-and-drop development environment.


Industrial automation systems are still relatively closed architectures when compared to modern computing technologies that leverage the talent and innovation of an ecosystem. For example, the industrial world does not have large ecosystems for applications, like Apple and android. OPC UA is the only open industrial standard that is compatible with the general computing industry web services infrastructure. IEC 61131-3 and PLCopen standards for programming are adopted at various levels by some automation vendors. The PLCopen XML interchange standard provides a way to interchange programs between vendor’s products, and simulation and modeling programs.

Early Adopters & Laggards

Automation analysts and vendors frequently talk about users that are innovators, early adopters, late majority and laggards for adopting automation technology. I think a question users may want to ask is, “Which automation vendors are innovators, early adopters, late majority and laggards?” In my opinion, this is an important consideration because it determines if your automaton systems will continue to be effective and competitive. The computer industry has proven many times that no single vendor can provide as strong a solution as an ecosystems of suppliers empowered by open architectures.

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