This article appeared in Machine Design and has been published here with permission.
It’s fair to say that Industry 4.0 and all its various acronym-laden offshoots have had a staggering impact on just about every facet of industry.
As a direct result, digital transformations have dominated headlines for the last few years, as data becomes the new protagonist in the drive to cut inefficiencies, reduce downtime, boost throughput and maintain quality. In a nutshell, more data from more places means greater insights; greater insights lead to better decisions; and better decisions result in enhanced operational effectiveness.
Thanks to these newfound data-based capabilities, many existing technologies and approaches have been left in the wake of the new digital paradigm; but there are some that are arguably just starting to realize their full potential. And in the case of distributed control systems (DCS), this has been a story some 60 years in the making.
Sitting at the heart of countless manufacturing and processing operations, DCS technology has been with us since the 1960s. Indeed, some contemporary DCS solutions may still exhibit elements of their original make up. No matter their age or origin, though, their development paths were always closely coupled to the pan-industry needs to address and overcome the limitations of legacy control solutions, such as pneumatic and mechanical architectures.
The primary drivers back then—arguably the same as they are today—were the need for greater availability, reliability and flexibility in plant-wide control systems. And by delivering these capabilities very early in their life, DCS technologies have become the go-to solution for so many applications.
Over the years they have adapted admirably to all that industry can throw at them, not just in terms of digital technology, but also engineering methods, service capabilities and process evolution. Indeed, the timeline of DCS’s expanding capabilities could easily be used to illustrate the biography of industry in general.
And this latest chapter—although not the last—is certainly going to be one of the most exciting, as the DCS evolves yet again to underpin the flexibility and agility needed for companies to adapt to changing market, business and process demands—far more quickly and far more easily.
The Next Chapter in DCS
So, what does this new chapter look like? Thanks to industrial IoT (IIoT), Industry 4.0, far deeper and more widespread smart-device-level connectivity, and modern analytics, DCS has the opportunity to champion a revolution in the control environment, one that will lead to faster, more meaningful and more consistent decision-making, by both operators and autonomous systems that exploit the fascinating capabilities of machine learning and AI.
And it’s not just technology that is driving the further development. As a vendor of DCS solutions, we have to keep a very close eye on our customers’ pain points and then adapt our solutions accordingly. Indeed, it is these types of market demands that sit alongside technological evolution as major drivers in our platform innovation.
User-driven input from both individual companies and trade bodies is also occurring much earlier in the development cycle, which helps us proactively counter the tidal wave of demands and pressures they are facing, based on the new data-driven economy. Hand in hand with this we are also seeing major strides in process-level modularity.
Modularity is an interesting evolutionary case in point, to which DCS is having to adapt. With growing consumer demand for individualism and even hyper-personalization—especially in the pharma, food and chemical sectors—the requirement for smaller economical batch sizes is becoming commonplace. But in order to adapt quickly to these demands, process solutions have to be incredibly agile, in order that additional costs—ones that would make the concept unfeasible from a financial perspective—are not accrued in the batch and process set-ups.
This need has led to the emergence of plug-and-produce modular automation, which promises to deliver easier implementation, simpler scalability and faster changeover. A new standards-based approach being spearheaded by NAMUR is based around the exploitation and deployment of Module Type Package (MTP) architectures, which turn processes and automation infrastructures into subsets of easily configurable building blocks. Each discrete process step, machine or element is given its own identity and instruction set within an MTP “container.” These MTPs are then orchestrated by a supervisory system for which DCS is extremely well-suited in this new-yet-traditional role.
This new building-block approach is on course to revolutionize process-system design, with its open vendor-agnostic architecture attracting interest from many sectors. Interestingly, with procedures being driven by a controller or logic engine, it makes sense that it can fold into existing DCS architectures to serve as a modular orchestrator, creating hybrid control models that combine “traditional” with new.
Security by Design
Connectivity has always been key to the efficacy of a DCS solution, but in the modern digitally transformed environment, as this connectivity grows almost exponentially so does the threat of cyberattacks, as more end points and threat vectors are created. As a result, we have to balance cybersecurity needs with the preservation, availability and interoperability of systems. As part of a holistic approach to network security and ruggedization, if users follow cybersecurity standards such as ISA, IEEE and IEC in all phases—from design, through development and onto maintenance—the DCS becomes secure by design.
DCS technology is also adapting to cater for the new needs of the new workforce. Across the globe, as seasoned engineers and operators retire, industries are hemorrhaging knowledge that has been gained through decades of tactile relationships with plant hardware. The new generation of engineers has a commensurate level of intimacy, but with more modern technologies, and are comfortable controlling most of it with their thumbs. But they need history to teach them. As a result, knowledge capture is a growing discipline, and when contextualized can be built into DCS logic and even imparted to new staff through augmented- and virtual-reality overlays.
If you consider all of these newly required capabilities, there’s nothing new in there; they are simply an adaptation and evolution of what DCS technologies have always delivered: expansion, simplification and greater connectivity. There is considerably more data flying around, but thanks to Moore’s law and far superior data-handling protocols, this data can be collated, analyzed and shared in a meaningful way with all elements (human or otherwise) of a production or processing environment.
The reason DCS is still with us is because no one has come up with anything to replace it; they have just created better DCS platforms. Old-school “this is how we’ve always done it” approaches are usually frowned upon and often don’t sit nicely with younger and possibly more enlightened engineers. But in this case, we have to make an exception.
Even with the cloud and edge computing, DCS is just relying on an even greater amount of distributed data sources, some of it geographical and some of it far cleverer and far more useful to modern production environments. As industry’s steady “hand on the helm,” DCS technology is unlikely to go anywhere soon, especially as it undergoes a renaissance adapting to new data-driven capabilities. Its initial reason for existence is still as relevant as it was all those years ago, and it will be for many years to come.