While the Purdue Model has long been a standard for structuring industrial networks, it has several limitations in today’s evolving digital landscape. Originally designed in an era before IIoT, cloud computing, and big data analytics, it struggles to accommodate modern industrial needs.
One of the main limitations is its rigid hierarchical structure, which can slow down real-time data access and integration. Additionally, as more OT systems connect to the cloud, the model’s strict segmentation can become a bottleneck for innovation.
Newer approaches, such as Unified Namespace (UNS) and Industrial Data Platforms, are addressing these challenges by offering more flexible, event-driven architectures that allow for greater scalability and interoperability in digital transformation efforts.