The New Era of Automation Architectures: What does it mean for users?

  • February 27, 2017
  • Feature
The New Era of Automation Architectures: What does it mean for users?
The New Era of Automation Architectures: What does it mean for users?

By Bill Lydon, Editor,

It is not news that the industrial automation industry is in the midst of sweeping, fundamental change. I have been writing for years about the coming changes to industrial automation system architecture and now we’re finally seeing that evolution starting to occur. The application of revolutionary new concepts and technologies, including the Internet of Things (IoT), sensor advances, embedded controllers, and other technology improvements, are rapidly driving this evolution. 

5 years ago, I wrote the article: Simplifying Automation System Hierarchies, which discussed the looming changes in industrial automation architecture, due to the dramatic growth and influx of the system concepts and technology advancements, that were then in their infancy.  The article further discussed the pending collapse of the Purdue five-layer architecture model, a model that has been reflected in most traditional industrial automation systems configurations.  The latest automation innovations have enabled users to create more responsive system architectures, which have been driving increased reliability and performance, in addition to lower software maintenance costs. Each new innovation provides even more building blocks to further evolve system architectures and spawn nearly exponential innovation in industrial automation. This article will further discuss the ramifications of these changing system architectures as well as links to other articles describing some of the products and developments that have resulted from and are spawning more of these changes. 

What does this evolution mean for users?

Existing Systems Will Slowly Fade

This isn’t an overnight process. Installed systems will certainly be kept in place as long as they are productive, financially viable investments just as mainframe computers and minicomputers remained in place when they were still sensible.   Yet, the newer innovations can definitely help extend and improve these systems, as add-ons which increase functionality and value.   Many established suppliers have a tendency to view new technology additions as unattractive, for a range of reasons, until they come out with their own version. We saw this trend recently as well, through the initial resistance of traditional suppliers to replacing proprietary HMI hardware and software with PCs and Windows-based software.

Shortening Lifecycle Curves

The influx of new technology also has the capability to shorten the lifecycle curves of existing systems significantly, if they add value and lower the ongoing cost of ownership.  When this tipping point is reached, it will accelerate the adoption of new technology and decrease the lifecycle of existing installed solutions.  Again, the computing industry provides a viable example. The old model of enterprise computing required programmers to write computer code for reports and analysis based on the user’s requirements, a process which was labor-intensive and took far too long to achieve results.  End users who performed analysis on PCs using spreadsheets, were able to significantly lower the cost of accomplishing these tasks while also providing immediate actionable results.  The impact of this decreased cost, in both time and money for the business community, signaled the end of large data processing departments. You can even find a prominent example in your own home. How many people no longer use cameras, given the convenience of today’s smartphone camera technology and instantaneous sharing ability?

Big Data, Analytics, Edge & Fog Computing

Big data & analytics have served as one of the largest areas of potential to improve the operations of discrete manufacturing and process plants. Yet these advancements also require new computing models.


Applications that do not need to be synchronized with plant operations in real-time can reside in on-site servers and/or cloud services delivering new operational insights and predictive maintenance.  This function can be value-added easily to existing systems.

Edge & Fog Computing

We are just starting to scratch the potential gains in efficiency and profitability for discrete manufacturing and process plants, through the application of big data and analytics, synchronized in real time with operations.  This application is accomplished by using edge computing at the sensors and actuators, in order to perform the real-time analysis and make decisions that change operating parameters.  Another building block for these architectures is fog computing, which is between the edge devices and the cloud. Fog computing is designed to bring the high-performance application of big data and analytics closer to the edge.  Today, these functions are starting to be performed in newer, more powerful industrial controllers and PCs, in harsher environments, delivering further insights into operations.  This has only been possible through high-performance embedded computing and low-cost high-speed communications.

Communications to Everything

The new industrial automation architectures are enabling edge devices to communicate to any level in the hierarchy.   The sensors and controllers, at the edge, are able to communicate information to all levels directly using the appropriate methods and protocols.  Yet, today's multilevel hierarchical computing model still requires field data to pass through multiple computers, and layers of middleware software before reaching the enterprise and remote experts. This creates complicated brittle architectures, which can lead to significant increases in cost, risk, ongoing configuration control, and lifecycle investment.  In contrast, the new distributed model brings computing to the point-of-use, streamlining the system architecture at a significantly lower lifecycle cost.

Holistic & Adaptive Manufacturing

Industry 4.0 and related initiatives create holistic and adaptive manufacturing, delivering a logical next step for industrial automation systems to achieve more responsive and efficient production.

Organizational Competitiveness is at Stake

Companies that do not research and take advantage of the appropriate disruptive innovations are likely to become stagnant and see themselves leapfrogged by more advanced competitors.  Conversely, companies that leverage disruptive innovations are positioning themselves to become leaders in their industry.  There are numerous historical examples that saw people and companies take the risk to leverage innovative thinking and technology and revolutionize not only their business but the industry at large. These examples include:

Henry Ford - Ford dominated the early automotive industry with the world’s first moving assembly line.

Andrew Carnegie - Producing steel more efficiently using technology including the Bessemer process and innovative material handling systems.

Federal Express - Leveraged bar code and computer technology to achieve dramatic growth. 

Change Agents

This is NOT a no-brainer. Automation professionals need to be change agents, do the research and understand the new technologies to determine if they can be effectively used to improve results in their companies.  We at are constantly working to bring you the latest and best information for automation professionals to be able to make the best decisions for your future.

Related Articles

Did you enjoy this great article?

Check out our free e-newsletters to read more great articles..