5 best practices for how to justify, implement, ramp up, and successfully manage IT and OT convergence

But getting from here to there requires converging the traditionally separate realms of information technology (IT) and operational technology (OT). In a recent Foundry survey, 98% of organizations view IT/OT convergence as a priority, ranging from moderate to critical, with most indicating it is high (45%) or critical (40%).

With IT and OT working together, organizations can optimize their processes, minimize costs, and deliver exceptional products and services by ensuring seamless information and data flow across product life cycles.

To succeed, businesses need to break down the barriers that have historically impeded IT and OT system integration and interoperability. Those barriers are found throughout the supply chain, logistics and distribution, manufacturing and quality processes, and product management activities. Without integration, IT and OT systems, people, and processes cannot fully interoperate. Bridging this gap requires a new way of thinking about data.

Data-driven strategies are essential to improve plant operations and generate digital services revenue beyond the point of sale. That’s increasingly important with new technology levers coming onstream, such as blockchain, 5G, immersive experiences, generative artificial intelligence (AI), digital twins, and more.

Best practice #1

Establish standards for conformity, integrity, and reliability to increase efficiency throughput. It is essential to develop a standard definition (data model) of the enterprise that spans IT and OT. Consider the semantics and ontology that will be shared between the different functions. At the same time, it’s important to follow all data governance policies. Best practices include:

• Classify data by asset class
• Consolidate data from various feeds
• Focus on how data is consumed by business processes

Overcoming obstacles and challenges

Digital transformation fueled by AI, edge computing, and cloud technology is driving new capabilities within the manufacturing and retail sectors. Advanced manufacturing technology infrastructure is essential to navigate a journey that harnesses data to create better business outcomes

The siloed approach to factory operations creates challenges when integrating legacy equipment with modern capabilities. The lack of integrated management processes is a top management and operational challenge for manufacturers, according to the Foundry survey

Digital technologies are rewriting the rules of how physical and virtual products are engineered, manufactured, and used. IT and OT convergence is essential to merge business and operational requirements, but many organizations are hesitant to implement changes that could temporarily disrupt operations— even though long-term benefits far exceed short-term pain points.

Aligning Modernization and Migration

A world leader in the design, manufacture, and delivery of aerospace products and services wanted to breathe new life into its aging product lifecycle management (PLM) and engineering IT portfolio, which was becoming increasingly expensive to operate. The current PLM program leveraged multiple legacy platforms, in turn negatively impacting aircraft design and development. A set of modernization and migration strategies delivered multiple benefits, including:

• Heightened innovation capabilities and reduced cost of development
• Quicker time to market and reduced overall costs
• Reduction in overall standard part request process cycle times
• Enablement of release on demand and faster deployments
• Effective data management and traceability

5G-Enabled Automation

One example of 5G innovation involves a first-of-its-kind 5G-enabled automated hoisting solution. Schneider Electric, Capgemini, and Qualcomm joined eorts on designing and installing the solution at Schneider Electric’s hoisting lab in Grenoble, France

Replacing wired connections with wireless and unifying existing wireless connections from Schneider Electric’s industrial automation system, the 5G Private Network solution demonstrates how it can simplify and optimize digital technology deployment at scale across industrial sites—from steel plants to ports

Many organizations, for example, are overly reliant on third-party customized legacy solutions. But software-defined solutions running on general-purpose compute systems have emerged as an effective lever to accelerate convergence. Digitalization is a powerful force for change as manufacturers seek to boost their operational excellence, production efficiency, and sustainability.

Best practice #2

Implement predictive maintenance solutions before hitting the field. It’s estimated that companies will save up to $630 billion by 2025 thanks to predictive maintenance, which reduces breakdowns and increases component lifespan.

Using predictive maintenance solutions enables engineers to catch errors, flaws, or damaged parts before they negatively impact machinery or operational workflow or get deployed to the field. Catching and fixing defects and production errors in-house is much easier and less expensive. Once released to the field, the scale of costs for fixes or a physical recall becomes exorbitant.

Best practice #3

Adopt edge platforms that protect code and data in several scenarios: at rest and in transit between storage and memory; in transit between processes; and during execution. Converged edge solutions bring IT, OT, and communications technology workloads together to simplify device and workload management and enable new cloud-native capabilities. Edge computing also frees up backend computing power and enables near real-time responses.

Including edge in an internet of things (IoT) ecosystem addresses specific use cases, such as massive data processing and management of centralized gateways—for instance, in an oil refinery—where multiple sensor nodes work on different technologies to communicate to an edge gateway for quick data analytics and processing. Edge also supports device and data security better with a zero-touch provisioning solution.

Innotech ® and Audi Team Up to Transform Manufacturing

Innotech is taking analytics to the edge and helping Audi automate and enhance critical quality control processes in its factories. By creating a data-driven platform solution, Audi can reduce human error and ensure its cars are built with even more accuracy and precision.

Best practice #4

Ensure low latency for critical and timesensitive applications. Reducing latency includes investigating emerging 5G options that provide seamless connectivity and massive computing capabilities to accommodate the deluge of data generated by industrial sensors.

The new 5G global cellular communications standard offers higher speeds and capacity, lower latency, and more reliability. This in turn paves the way for many more innovative use cases, such as robots, automated machines, greater factory automation, and augmented and virtual reality— delivered at scale and cost effectively, through a multipurpose network of unprecedented flexibility.

Key drivers for the adoption of 5G or re-evaluation of existing connectivity technology include:

• Operation of large fleets of automated guided vehicles (AGVs) and autonomous intelligent vehicles (AIVs)
• Connected driving environments, connecting vehicles, infrastructure, and people
• Connected and augmented digital worker solutions that require high video quality and secure connectivity
• Retrofitting/augmentation of IoT sensors

Best practice #5

Accelerate adoption of digital twin solutions. Digital twins are virtual replicas of physical systems that can model, simulate, monitor, analyze, and constantly optimize the physical world. They can be used for virtual testing to increase cost savings and evaluate the ROI of initial investments prior to factoryfloor implementation.

According to Capgemini, organizations working with digital twins have seen a 15% improvement in key sales and operational metrics and an improvement upwards of 25% in system performance. The organizations have also seen an improvement of 16% in sustainability, according to this report.

Organizations use digital twin capabilities for new production lines or greenfield plants, including virtual commissioning and complex simulations. Data sets from existing installation and post-production use can be used to optimize processes and calculate “what-if” scenario outcomes.