Basics of the digital transformation (DX)

A digital transformation (DX or less commonly DT) is the application of software, programmable hardware, and operational technologies (OTs) to fundamentally transfigure a company’s operations and end products for the better. DX programs can be undertaken by industrial organizations, machine builders, or a vast array of other businesses; the involved OTs typically include machine-monitoring systems, connectivity, and online web and cloud access —especially that via tools with internet of things, IIoT, or Industrie 4.0 functionalities. The most successful digital transformations engage every employee at the organization from management to seasonal plant personnel and continually evolve in response to quantified results and personnel feedback.

Process workflow optimization image: Tsingha25

But whether instituted by a team internal to an organization or hired consultants, digital-transformation initiatives can face pushback at established companies — especially from naturally skeptical engineers. Exacerbating this issue is the way in which products supporting DXs are inherently reliant on the adoption of complementary elements to work … so a given smart sensor (to give one example) can require adoption and integration of dozens of other disparate components and elements to support a grander initiative. In some cases, the suppliers of such components and tools eschew marketing that touts IoT functions for communications that instead address the specific business concerns of an industry.

Both discrete automation (for the machining, assembling, otherwise working, and transporting separate discrete workpieces) as well as process automation (for the distillation or other use of liquids, systems of fluids, and other batches subject to continuous chemical reactions, temperature controls, and metering) have benefitted from the burgeoning benefits of DX. In this Design World article, we primarily focus on discrete automation examples.

As we’ll explore, suppliers best equipped to support digital transformations of business models are those with long histories in engineering and manufacturing and extensive product lines with smart products and services leveraging data analytics.

Beginning a digital transformation

Though all organizations have mission-critical issues that (if solved) could mean business-model quantum leaps, those issues shouldn’t be tackled in nascent DX trials. Starting small on more manageable processes needing improvements is the wisest approach to an inaugural deployment. The first step in a successful DX is to define lingering problems internal to a company or affecting the industry at hand as a whole. Despite the industries’ differences, common challenges are found in industrial automation, energy management, building automation, data centers, and public utilities.

Design World uses many examples involving discrete automation to illustrate the possibilities of DX. Here, smart motion controls work by accepting sensor, switch, and encoder feedback and serving as (or triggering the signal-amplifying (amplifier) action of motor controls — all traditional functions. They also serve an additional role of connecting machines to enterprise-level systems.Those most familiar with the issues needing solutions are information technology (IT) personnel as well as those directly supporting operations and line-of-business services. They’re also the most likely to have connectivity wish lists — whether for:

Automation functions (via device, control, machine, and cloud integration) or
Data access and use so important to IIoT functionalities.

For the former, leading trends include the rise of edge computing (including the use of industrial gateways) as well as services that support cloud connectivity, Ethernet-based networks, wireless communications for industrial components, various forms of standardized protocols, open-source programming code, and unifying software environments to facilitate interoperability.

For the latter, automated company data sharing along with advanced analytics as well as artificial intelligence (AI) are the IoT capabilities leading DX efforts. The connectivity-heavy nature of such DX implementations means that many organizations fund and support them through IT departments who must in return stay current with the IoT networking, data storage, and improvement programs the organization develops, deploys, or employs.

Where organizations involve line-of-business teams in DX initiatives, they can often help solve challenges faced R&D, engineering, operations, maintenance, and corporate teams. Solving such operational issues ultimately benefits end customers and other external entities that interface with the organization.

Where IoT meets the physical world

Just consider a discrete automation system’s edge devices — the actuators, sensors, and connectivity components including gateways and motor-mounted controllers with computational resources to eliminate data bandwidth and latency issues. Their location at the furthest reaches of machinery means their processing power is well placed to filter and analyze data before it’s sent onward to central controls or the design’s cloud presence. However, the usefulness of edge devices ultimately relies on interoperability with multiple machine systems.

When conjuring such systems, most engineers are likely to picture the traditional automation-communications pyramid. Such architectures include data exchanges between field-level sensors and higher implementation layers … as well as some communications between controls … finally rising to the pinnacle of the enterprise level. But several technologies have facilitated distributed and intelligent systems with flatter machinery communication structures:

• Today’s software (along with industrial apps not unlike those for consumer-grade mobile devices)
• Newer options such as cloud services — as one networking example
• Hardware such as programmable automation controllers (PACs) and smart field devices — as two component examples

These technologies have changed the structure of the intelligent factory floor — especially over the last decade.

What’s the point of all this? Well, smart factories (sometimes billed the Factory of the Future) will increasingly use wireless connectivity including 5G as well as distributed intelligence and edge computing to:

• Allow manufacturing to be more responsive to change
• Impart more flexibility in production planning
• Predict maintenance and failures before critical work stoppages.

These features help reduce warranty, waste, and downtime costs while improving worker safety, ideally with IoT implementations that satisfy the objectives of machine builders as well as end users.

Specific digital transformation benefit examples

The most effective DX implementations are those that are operable across business systems (especially as the IIoT continually evolves) while prioritizing cybersecurity protections. Component suppliers and solution vendors most capable of supporting machine builders and plants with DX efforts are those connected to comprehensive partner networks that standardize on certain protocols, software tools, and design ecosystems. These in turn allow assembly of various vendors’ technology elements to build customized end-to-end IoT solutions … in some cases, complete with continued support from licensed integrators or digital services designed for a given industry.

But what are the benefits to OEMs and facilities that adopt DX approaches?

Well, 21st-centuty demand for customized end products (from foods to electronics to homes) is supported by DX initiatives, as connected companies are the nimblest and most capable of flexible production routines.

In some cases, DX enables new business models that turn data (processed by analytics or AI) into salable products. This can take the form of subscription-based or value-add machine-monitoring products. The benefit to end user is the remote fixing of problems without having to wait for a technician to fly or drive to the facility.

Digital transformation solutions are nearly always scalable, allowing OEMs and end users to experiment with a new system in one location and then leverage what’s designed and learned in more places later — often with significant savings from the economy of scale.

DX also frees automated facilities from classical single-file production lines that are limited by inherent inefficiencies and (especially in manufacturing) workforce shortages. AI especially complements personnel functions and enables more nuanced factory flows — freeing humans from data analysis and assessing situational contexts to serve as the so-called missing middle and inform (or sometimes even trigger) real-world actions.

Embracing supplier partnerships for DX efforts

In some cases, long-term partnerships with industrial suppliers can help vendors and end users keep current in their DX efforts. Such arrangements deemphasize product-centric businesses and emphasize support services and operating platforms. What’s more, step-by-step design approaches (like production approaches) must yield to more flexible design and prototyping approaches. Here, the typical trial-error iterative process involving mostly siloed in-house design teams is replaced by open and holistic design work.

Supporting such approaches are so-called design ecosystems and platforms from industrial suppliers. To complete such offerings, suppliers often partner with professional services companies specializing in digital services that are applicable to industrial automation. The result is an array of throughput analysis, predictive maintenance, asset tracking, customer service, and energy optimization tools targeted to specific automation operations. The largest machine builders with long-term relationships with suppliers can expect help in analyzing business problems as well as tailor-made DX solutions.

Areas of OT/IT convergence

Whether led or informed by the organization’s IT department, DX efforts always include integration of shot-floor operational technologies (OT) into business IT systems. Smart connection of plant-floor OT to the enterprise-level IT helps organizations enjoy all the benefits of digitalization. Edge-computing technologies help link such OT and IT systems. This so-called OT-IT convergence addresses how these separate breeds of data-handling systems traditionally have very different processing structures — with the former increasingly expected to process and transmit data in realtime (or nearly so) and IT systems sampling and processing much more slowly. Cross-capitalization of both systems’ data (in some cases, massive volumes of unfiltered data) requires translation and interpretation to glean information relevant to the operations at hand. Cloud-based computing can help aggregate, manage, filter, and analyze such data. Otherwise, local platforms are needed to inform production adjustments in realtime.

Leveraging digital twins for DX initiatives

The use of so-called digital twins (or virtual or digital replicas) is core to the digital transformation (DX) of industrial automation. These digital twins — essentially software-based copies of real-world machines, processes, systems, operating environments, and products — are exceptionally accurate. That’s because digital twins are based on massive amounts of data collected from previous designs’ performance; feedback from sensors on installed equipment; and advanced replication coding. The result are models that let organizations explore, control, and optimize designs in efficient and cost-effective ways.

Use of digital twins is a core approach in the digital transformation of industrial automation. Image: Ekkasit919

In addition, digital twins support communications between interconnected IIoT systems. That’s because these digital models tend to standardize the programmatical descriptions of component parameters and interrelated definitions. Ultimately, that in turn lets operations output product with just-in-time approaches in smaller batch sizes. Digital definitions of interconnected machine modules and controls also make quick changeovers and reconfigurations (say, to temporarily output a specialty product) more feasible.