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Bridging the IT and Operations Divide in Manufacturing

Christine_Boles
Employee
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Manufacturers accelerate digital transformation and streamline operations with IT/OT convergence at the edge

Manufacturers’ products, from silicon chips to cars to robots, are becoming more complex. Manufacturing information technology (IT) staff are dealing with huge volumes of data from the testing of advanced features, modeling and simulation, and increasingly intricate development processes and applications. Operational technology (OT) staff are responsible for hundreds of complicated machines and upwards of millions of sensors. A new paradigm shift toward operational control enabled by intelligent edge applications is forcing IT and OT—historically disparate worlds —to converge.

 

Attaining the vision isn’t easy

Manufacturers recognize the potential benefits of IT/OT convergence, including operational efficiency, cost control, and better use of data. For example, using edge analytics and machine learning, Audi’s Neckarsulm factory implemented a solution to inspect 100% of the five million welds they make each day while inferring the results of each weld within 18 milliseconds. Audi was able to reduce labor costs by 30 to 50 percent, freeing employees for other valuable opportunities within the company.[1]

 

However, achieving seamless IT/OT convergence is proving challenging for many manufacturers. According to The Manufacturer, only 23% of manufacturers have achieved more than a basic level of IT and OT convergence, and less than half (42%) believe that their IT and OT visions are aligned.[2] Driving real business outcomes through IT/OT convergence requires fundamentally new ways of handling data, environments, and users than those for traditional applications and centralized data centers. Manufacturers face several hurdles:

  • Making sense of data. Edge solutions force a wide swath of machine- and people-generated data together. The variances in data structure, velocity, and volume make harnessing and understanding it complex—which makes it difficult to choose the best use case for the highest and most immediate business return. Multiple proofs of concept can waste valuable time and resources.
  • Integrating with legacy infrastructure and operational workflows. Nearly all edge deployments involve legacy equipment that was not designed with connectivity in mind. Managing both new and old equipment simultaneously, including a large number of devices, is a complex task.
  • Securing the edge. The scale of edge infrastructure and devices outside a centralized data center introduces significant complexity in securing both digital and physical environments. The expanded attack surface brings greater exposure to threats like distributed denial of service (DDoS) campaigns, data theft and leaks, and third-party vulnerabilities. Emerging solutions that attempt to solve cybersecurity concerns created by distributed virtual networks are often immature and require combining multiple vendor solutions.
  • Navigating a fragmented ecosystem and avoiding vendor lock-in. The edge involves a wide variety of use cases and workloads. Without a common, open standards-based platform, the ecosystem is often fragmented into dozens of possible solutions, with implementations requiring collaboration among several providers. Proprietary solutions can make it hard to pivot when markets and business demands change.
  • Developing and deploying distributed applications. Moving to the edge adds more nodes, operating systems, applications, types of code, compliance restrictions, and computing architectures. Some of the technology built for central clouds can’t simply be extended to the edge. The new tooling and platforms needed to handle this integration complexity have been immature to date, making edge development, management, and orchestration a significant challenge.  

 

Bringing the IT and OT worlds together

A recent survey conducted by Foundry and commissioned by Capgemini and Intel underscores that manufacturers seek to create an integrated, interoperable, and data-driven model powered by IT/OT convergence. In fact, 98% of the survey respondents indicated they would prioritize IT/OT convergence in 2023.

 

In the survey, 53% of respondents indicated that investment decisions for both OT and IT are made by a shared services or a designated corporate function, while 42% said investment decisions about OT systems are coordinated across multiple facilities, plants, and delivery systems through shared services organizations or a designated corporate function. The majority of survey respondents (88%) indicated that a dedicated team or role is necessary to support IT/OT convergence and create the advanced manufacturing technology infrastructure essential to harness data to create better business outcomes, which can include the following:

  • Highly optimized and automated production does more with less: Consolidating distributed workloads on a single, software-defined industrial PC makes manufacturing more efficient and adaptable. Smart robotics speed production, increase product quality and adjust to real-time shifts in demand and gaps in highly skilled labor.
  • In-line quality control and condition-based monitoring enable zero machine failure: Visual inspection and quality control during the manufacturing process, versus downstream, is a game-changer. Using computer vision and other AI techniques as part of control systems can validate features and check for defects in real-time.
  • Robotic process automation solves cost and labor issues: Robotic process automation (RPA) systems read constant streams of machine data to flag anomalies, perform raw materials checks, and track production hours and materials used, requiring tremendous amounts of low-latency compute.
  • Zero-accident environments: Autonomous mobile robots can move heavy objects while computer vision enabled cameras quickly identify dangerous anomalies.

Standards and open platforms are key

As mentioned earlier, IT/OT convergence and intelligent edge solutions require a complex mix of technologies, most of which are outside the expertise of manufacturers. For example, edge-native compute is built on a distributed network fabric provided and managed by global telecommunications providers. System integrators have industry-specific expertise, but no converged, extensible platform from which to build. How to best manage and secure deployments can be an exercise in navigating multiple, often immature offerings.

 

Challenges associated with integrating IT and OT systems are being mitigated by the emergence of unification and standardization. One example is the ISO 23247 series, which will help simplify and harmonize the landscape. In addition, new solutions are becoming available, built on open architecture. These solutions will enable integration of data-centric IT protocols into legacy machines through virtualized applications.

 

Intel technology powers the world’s clouds, networks, and enterprises with a common platform. We offer manufacturers the experience gained from years of work solving critical operational and IT divides, intense involvement in open standards bodies, and more than a decade of driving foundational networking and AI technology shifts.  We can provide rare insight on how to achieve industry 4.0 and IT/OT convergence—and we offer it to you through an unrivaled global ecosystem of solution providers.

 

For a list of best practices for successful IT/OT convergence and more insight into manufacturers’ motivations and challenges, read Foundry’s full report “Bridge the Divide Between IT and OT.”

 

[1] Intel, March 2020, “Audi’s Automated Factory Moves Closer to Industry 4.0.”Results may vary.

[2] The Manufacturer, September 2022, “Current state of IT & OT convergence among manufacturers revealed in new report.”

 

About the Author
Christine Boles is a Vice President in the Network & Edge Group (NEX) and General Manager of Intel’s Federal and Industrial Solutions. Her organization is responsible for Intel’s NEX Federal and Industrial business within the aerospace, manufacturing, energy, logistics and commercial building segments, including the product and ecosystem strategies for this rapidly evolving space. Boles joined Intel in 1992 as an application engineer for 16-bit microcontrollers. For almost 30 years, she has led development, delivery and the enabling of customers and ecosystems for Intel based solutions in multiple leadership roles. These solutions span a broad range of embedded and internet of things applications across many industries, including communications, storage, retail, imaging, and commercial buildings. Boles holds a Bachelor of Science in Electrical Engineering from University of Cincinnati and an MBA from Arizona State University.