IIoT: Collecting information on all physical assets in real time
Convergence of IT and OT Requires Digital and Industrial Expertise
Connectivity and Visibility Achieve Digital Transformation

The industrial world is enthusiastic about digital transformation. Digital transformation involves integrating IT (Information Technology) and OT (Operation Technology), previously considered separate disciplines, in industrial settings.

The convergence of the digital world (IT) and the physical world (OT) generates massive amounts of data. The digitalization of industry, represented by the Industrial Internet of Things (IIoT), relies on sensors to collect real-time information from all physical assets, serving as the foundation for data analysis for monitoring and maintenance, as well as for production efficiency and business innovation.

As AI expands across all industries, related technology companies are also experiencing a heyday. Most IT companies are pushing AI technology to the forefront, and cloud computing service providers and hardware companies are also competing with solutions optimized for AI support.

Fully integrating these two vastly different elements—IT and OT—requires both IT digital expertise and industrial field expertise, requiring an end-to-end solution that spans everything from factory production facilities to advanced data analytics.


Digitalization and digital transformation are different.
While digital transformation is a recent hot topic, the industry has been pursuing the digitalization of factories and other industrial sites for decades. Digitally integrated process transmitters and control devices are the result of this effort.

Transmitters are a key component of measurement systems used to monitor and control industrial processes. Digitalization makes process transmitters installed in industrial settings inherently smart.

However, integration with digitalization is not so straightforward. Industrial sites around the world are equipped with massive production facilities. Most production facilities outlast IT equipment, leaving a significant portion of them comprised of legacy systems and devices from before the digital era.

It's not just systems and equipment. Industrial applications are made up of smart things, with everything embedded with data. Countless objects, including power and vibration monitors, temperature valves, and various devices, are connected. Connecting all of this means connecting a variety of industrial protocols, commercial solutions, and a vast list of devices as if they were built that way from the ground up.

Digital transformation in industrial settings hinges on connectivity with existing assets. This connectivity not only extracts more productivity and value from existing production equipment and facilities, but also revitalizes outdated infrastructure. Companies can quickly connect critical data across all assets and production sites, enabling them to instantly monitor performance, predict equipment performance, and understand the performance of physical assets and digital systems within the production site through a single, integrated source of information.

This connectivity also allows for the rapid deployment of core applications, providing crucial insights to decision makers from executives to production lines. Companies can now understand what's happening in the field, what's broken, when maintenance is required, and how to respond.


What if IT and OT were connected? We need to analyze it!
The interconnected world of data has transformed not only people's daily lives but also corporate operations. Everyone's expectations have also shifted. Customers, partners, employees, and all other stakeholders now demand tailored products, seamless and personalized experiences, and, above all, instant access. Having solved the connectivity challenge, companies must now embark on a new journey of data and analytics.

Enterprises must connect IT and OT, enabling users to access data and insights from multiple facilities and devices. They must create and visualize a so-called "single source of truth" (SSOT) for this data to support better decision-making. Building on this foundation, they must actively adopt innovative technologies like AR to maximize efficiency.

Traditional industrial automation has been implemented on a per-product basis, per production line. Therefore, even if the entire production site is automated, it's impossible to understand the entire factory's production cycle, inventory status, or track data fluctuations. Not only is interoperability between automation systems impossible, but from a data perspective, the entire factory or facility is essentially a collection of isolated silos. Data sharing and integration through IT systems is inherently difficult and costly.

The challenge doesn't end with breaking down silos between systems and organizations through standardizing automation engineering and interface construction. Integration with Manufacturing Execution Systems (MES) is essential to unlock actionable insights, and AI and machine learning must go beyond automating data collection and analysis to enhance the value of data, extending beyond predictive analytics. Incorporating AR technology not only increases data visibility but also improves the efficiency of information sharing and training.


Four Challenges of Digital Transformation
Rockwell Automation, an industrial automation and information solutions company, has launched 'FactoryTalk InnovationSuite' to accelerate the digital transformation of companies, and has presented four challenges that companies must solve to achieve digital transformation.

First, real-time monitoring of production and performance is essential. Companies require real-time insight into their production processes. If they cannot detect and respond to issues as they arise, they face unexpected downtime, higher operating costs, and waste. Managing various systems with inconsistent regulations exacerbates the problem. Effective operations require easily accessible, comprehensive data insights.

Next is proactive maintenance. While regular maintenance can help maintain equipment, unnecessary maintenance can also lead to unnecessary costs. Proactive maintenance requires monitoring equipment and comparing its performance with historical data. This comparison allows for early detection of maintenance needs and, by performing maintenance only when absolutely necessary, reduces costs. Advanced analytics can also help you identify the root cause of problems before they occur, further strengthening your control over your production environment.

And then there's digital work instructions. Paper and PDF-based documents are cumbersome to use and time-consuming to maintain. They're also difficult to search and understand, and costly to translate. Outdated printed materials can contain outdated information and lack the ability to capture step-by-step execution and inspection information needed to create an MES audit trail. All of this can hinder workers from accessing and utilizing the information they need. Digitized instructions improve performance by combining real-time and historical asset data to provide contextual information.

Finally, there's the integration of equipment/machine analytics. Siloed data can make integrating automation systems with IT systems extremely complex and costly. Without standardization in how automation is engineered and interfaces are built, businesses face conflicting operational metrics and significant downtime. By providing connectivity to hundreds of different protocols and devices and visibility through a user-friendly interface, you can easily identify and investigate devices hidden deep within the architecture, enhancing the completeness of your analytics. In particular, it frees end users from the burden of data integration, collation, and cleansing for analysis.


A business where everything is connected from A to Z
Enterprises will now need to empower their developers with operational intelligence to succeed. This will provide them with insights that can transform how they manage their entire organization, how their employees work, and how they deliver solutions to customers. This interconnected business model presents a tremendous opportunity for many companies, and to capitalize on this momentum, they must be prepared for innovation.