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IT/OT Convergence for Smart Manufacturing & Digital Transformation in Process Industry

Over the last few decades, life and business have changed significantly thanks to developments in ICT such as the Internet. With information on hand, work processes today are simpler and communication much easier than ever before, yet we continue to see massive improvements in the ways that technology can support our activities and decision making.

Within the process industries, it is often difficult to introduce big changes because of direct impacts on health, safety, and the environment as well as on production capacities. Even though the field is relatively conservative however, it is no stranger to the benefits offered by digital transformation, or DX, and IT/OT convergence.

In my more than 30 years of working in process manufacturing, I have focused on and remain passionate about information systems. Throughout my career, I have handled information sharing between business and control mechanisms—commonly known as manufacturing execution systems or MES—to support production management and operations teams. In each of these projects, information (or a lack thereof) has impacted our business objectives in many ways.

In the last decade, we have encountered variations on the theme of IT/OT convergence, including data integration, DX, and so on, but how is today different from previous years? I believe that while there are no substantial differences in basic concepts or principles, the way IT/OT convergence is initiated and applied today has evolved. So why is it so important now?

The drive for savings

As the unit cost for ICT including storage, calculation, and network communication dropped, the market opportunities for sophisticated software applications and algorithms to collect, integrate, and utilize data increased rapidly. Big data platforms, machine learning, and AI have gained traction in enabling cost reduction and work efficiencies, benefitting customers across multiple sectors.

Although success stories and use cases for other industries are widely available, the process industry has yet to fully embrace these technologies and benefits with proper assessment or an appropriate roadmap.

The increasing value of integration in the connected world

Given the pressures of tightening regulations and global competition, corporation- or country-level digital strategy to sustain business has become imperative. This kind of strategy requires the implementation of digital interfaces to connect multiple companies and/or departments in order to drive standardization, eliminate silos, and maintain shared corporate culture.

While this connectivity is established in the IT layer, it also provides a framework for OT, and communication happens not only between the IT and OT systems but also within them. It is important to note that, for OT systems in particular, enterprise competencies and unique business situations must be considered when establishing this connectivity which makes it an opportunity or a challenge in itself.

To add to the complexity, organizations must also think about the symbiotic use of data. One angle here is to link and transform OT data into IT data for real-time decision making. Other approaches include bringing IT data into OT without destroying its integrity and fully utilizing IT to improve OT activities. These angles and their potential outcomes are outlined below.

  • OT data ⇒ IT data: Real-time, accurate, and properly transformed information for decision making

  • IT data ⇒ OT data: Properly transformed, efficiently, and accurately delivered information to identify and synergize with relevant OT data

  • IT technology ⇒ OT applications: To achieve smart manufacturing, optimization, AI for diagnosis and prediction, and autonomous operations

  • OT data ⇒ OT data: Effective integration of OT data

Many use cases have explored this simple framework, and multiple organizations have realized efficiency and other improvements through this kind of IT/OT convergence and DX initiatives. Nevertheless, the process industries still have a long way to go.

Some existing example scenarios are

  • Real-time dashboards showing how production KPIs increase the speed of delivering information to the management layer;

  • The comprehensive definition of open and standard interfaces when integrating disparate systems to maximize the benefits of data exchange;

  • The implementation of wearable devices to resolve skills gaps or resource shortages;

  • The utilization of AI technologies for equipment condition diagnosis and quality management.

Some of these initiatives have gone so far as to improve business competitiveness, and organizations are starting to recognize the importance of IT/OT convergence to achieve a connected world.

The road to successful IT/OT convergence

It is no secret that improving business performance through technology is not 100% guaranteed. There are, however, a number of ways to improve the chances of success.

From a technical perspective, I have heard that more than 70% of DX and smart manufacturing activities result in abandonment or failure because of contradictory goals between orchestration and autonomy. Complex systems that include multiple functions and applications are required to be optimized both individually and collectively as well as synchronized as an entire structure. So, how can we balance the overall design and vision of a large system against the autonomy of each of its individual applications? While implementing an agile approach is tempting, managing complex systems goes beyond system architecture; we also need to consider organizational structure and behavior for an initiative to succeed.

Second, business process reengineering or BPR was previously introduced to achieve efficiency using IT systems, and it is now necessary to apply the same principles to the context of IT/OT convergence. Without a properly systematic approach, it is impossible to reap the benefits of any smart initiative, primarily because autonomous systems and organizations are so closely orchestrated with one other. It is therefore important to analyze the current operational context and its issues through establishing a common vision, achieving alignment on areas for organizational reform, and developing understanding of the As-Is with support from upper management.

Devising a systematic operational approach requires an objective and enterprise-wide viewpoint, typically achieved through the collaborative effort of internal cross-functional teams and/or third-party facilitators. Depending on the business objectives, the best way forward is usually for organizations to realize and agree that IT/OT convergence, DX, or smart manufacturing initiatives are not purely about technology selection and evaluation. While technology plays a key role in accelerating value realization, the first step is being clear on what the organization wants to achieve (To-Be) and the existing gaps across their people, processes, and technologies (As-Is). To gain trust and buy-in, it is crucial to reflect the concerns of the organization’s stakeholders and develop a common vision for improving the business.

Many technical barriers concerning data storage, processing, analytics, and AI have been eliminated because of the reduced costs of several elements. The process industry, however, is in a unique situation; despite the availability and relative cost-effectiveness of the Industrial Internet of Things (IIoT), capturing data and/or measurements in this context entails increasing the real-time data points used, thus increasing the associated costs. While increasing the types, frequency, and number of measurement points delivers several benefits such as increasing and broadening data collection from the source, these can actually prevent organizations from achieving smart manufacturing because incorporating more is not always necessarily smart. Instead, we must select the appropriate data that can be digitized by humans, robots, or other technologies such as digital twins, to complete a full picture of the organization, plant, or facility. The amount of relevant data collected can be increased cost-effectively by utilizing a smart mix of humans and devices.

Conclusions

  •  Changes in ICT have changed the way we live and work;

  • The digital maturity of the process industries is relatively low given their roots in asset and operational technologies which are generally traditional and longstanding;

  • Smarter manufacturing is increasingly mandatory due to tightening regulations, globalization, and digital maturity;

  • Many DX and smart initiatives fail through human reasons, and so the keys to success include

o    having a shared vision across the organization;

o    developing an objective and comprehensive understanding of the current operational context;

o    agreeing that digital initiatives are not just technology and evaluation activities but rather they touch on the organization, its processes, and its mindset; and

o    approaches to data collection and measurement should balance appropriateness and increasing technological capacity.

Yokogawa will help you develop a blueprint and program for smart manufacturing and organizational DX. As your trusted partner, we will work closely with you to assess your priorities and ultimately achieve your business objectives using our 3Ds model.

Yokogawa’s 3Ds Model for Digital Transformation

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