Building a Foundation for AI Transformation in Manufacturing
As the pace of AI development accelerates, industry leaders are embracing this technology as a strategic imperative, using it to transform their processes, improve their quality, and boost their bottom line. Companies looking to similarly embrace AI are best served building a strong digital infrastructure that prioritizes quality data, edge processing, and strong security. When done right, this digital infrastructure becomes the foundation for AI deployment, giving companies a secure, flexible platform from which they can easily adopt best-in-class solutions to gain the competitive edge.
Data Capture and Synchronization
AI will only ever be as good as the data it’s built on. In fact, industry reports suggest data quality issues are the leading cause of failure for AI initiatives. On one end, gathering data from equipment can pose significant challenges. Many manufacturing facilities operate on legacy systems that were not designed for AI integration. Organizations must collect and standardize data from equipment using any variety of communication protocols. On the other end, is data synchronization. This is the process of establishing consistency within data sets so they can be successfully used by machine learning models. This is far from a trivial process. Developers must account for a litany of potential challenges like network inconsistencies, data changes, asynchronous syncs, server errors and more.
Thankfully, solutions exist to simplify this process. Eurotech’s integrated hardware and software leverages a wide range of connectivity types and a large protocol library to streamline integration. Further, their solutions leverage digital twins to simplify data synchronization. These digital twins provide a single source of truth for the data across different devices and systems.
As AI solutions have matured, many applications are moving toward the edge. Edge AI can enable faster and more accurate data analysis and decision making by processing data locally and reducing latency. In turn, this processing speed can empower sensor-enabled devices to communicate and collaborate with each other, enabling more automation and flexibility in the end solution. Edge processing also provides additional protection to the end user. By processing on an edge device, operations can continue to run smoothly even if there is a network disruption or server failure by providing a backup or fallback mechanism. Further, Edge AI can protect the data and devices from cyberattacks by encrypting and authenticating data as well as limiting the data exposure to the cloud.
Operational Technology (OT) Security
With all the promise of AI, cybersecurity risks cannot be underestimated. To implement AI based solutions, companies must open OT systems to new, significant risks. OT based cybersecurity attacks are on the rise and can cause colossal impacts. Companies can mitigate this risk by building safeguards for each step of the solution – from physical hardening of edge devices to a secure ‘chain of trust’ for data communication. Thankfully, standards exist that outline cybersecurity best practices. Foremost among these is ISA/IEC62443, which covers every stage and aspect of industrial cybersecurity from risk assessment to operations. At Eurotech, we provide pre-built IEC62443 solutions, helping our customers ensure compliance and security from the start.
There is no doubt that AI is a powerful and disruptive technology that will reshape the industry. However, AI is not a magic bullet that can be applied without proper planning. Companies need to build a robust digital infrastructure that can support their initiatives and ensure their data quality, processing efficiency, and security. By doing so, they can leverage the full potential of AI and reap the benefits of this game-changing technology.