Ask anyone: We’re in the midst of a fourth industrial revolution. It’s not powered by steam, like the first; assembly lines, like the second; or even information technology alone, like the third. This paradigm shift is driven by a cluster of smart technologies, from the Industrial Internet of Things (IIoT) to AI-powered analytics to innovative networking frameworks. At the core of Industry 4.0, of course, you find automation.
But it’s one thing for a manufacturer to commit to Industry 4.0. It’s quite another to make the transition. The Global Lighthouse Network (GLN)—a research partnership between McKinsey and the World Economic Forum (WEF)—studies the development of Industry 4.0 around the world. As of 2022, GLN has identified only 103 “lighthouses,” industrial facilities said to have completed the Industry 4.0 transformation. Meanwhile, over 70% of companies are “still stuck in ‘pilot purgatory,’” says the WEF.
The challenge is especially steep for manufacturers. Technology updates can shut down production lines. New operational equipment is mind-bogglingly expensive. Worst of all, current computing architectures aren’t built for broad integration—an essential prerequisite for any smart factory.
The promise of Industry 4.0 is huge: faster time to market, lower production costs, better asset utilization, real-time business insights. All of these benefits rely on the lifeblood of digital transformation: big data. But even if they can collect that data, manufacturers often struggle to mold it into a usable form.
Here’s the key challenge manufacturers face as they transition to Industry 4.0—and how to solve the problem.
The Challenge of Industry 4.0 in Manufacturing: Achieving IT/OT Convergence
Operational technology (OT) includes all the hardware, software, and communications protocols that manage and control industrial processes. Information technology (IT), on the other hand, covers the computing systems and networks that transfer and process data. For decades, these fields have been stuck in their own silos, locked away from one another by incompatible protocols, high-latency networks, and different paradigms of data processing.
To achieve the ends of Industry 4.0, OT must share data with IT. Collecting frontline information—a particular advantage of IIoT—falls under OT’s mandate. Transforming that information into insight, making it usable in the broader sense of business, outside the scope of purely controlling the machines, is its job. Industry 4.0 projects aren’t possible if these two sides can’t communicate or interact to produce value to the company.
Traditional OT architectures were built to supervise and control industrial processes—not to share data widely. They use a handful of communication protocols (Modbus, OPC-UA, BACnet) that isolate their data into independent islands: data puddles, as the technologists call them. Even if you could connect OT and IT systems, high-latency, cloud-based networks with brokered traffic systems make real-time analytics impossible.
There’s good news too, though: IT/OT convergence is possible. You just need a new approach to networking, a communication protocol that flows seamlessly through both systems, and a common model to share and exchange data. Two technologies work together to accomplish all three goals: edge computing and the MQTT protocol.
IT/OT Convergence in Manufacturing: IIoT Edge Databases and the MQTT Protocol
A new approach to IT/OT convergence has to solve two problems at once. First, it must allow IT and OT systems to communicate freely. Second, it must enable the low-latency data transfer that’s essential for real-time intelligence. Here are the solutions for each challenge.
Bridging OT and IT with the MQTT Protocol
The first problem boils down to communication protocols, the file formats and formal rules that allow one machine to “talk” to another. As we mentioned, traditional OT protocols are locked into their own domains. Luckily, a better option has arrived.
For IIoT systems, MQTT is the ideal messaging protocol, and it’s quickly become the de facto standard in all sorts of IoT networks. MQTT is lightweight enough to work on the low-footprint data demands of IoT devices, including those with unreliable bandwidth. And you don’t have to shut down production to make the switch: MQTT clients can be installed on existing OT (including IIoT) systems. On the IT side, MQTT brokers can work alongside traditional cloud or on premise servers.
That takes care of the IT/OT convergence issue. Next, you need a network architecture that can handle all that MQTT traffic—reliably, securely, and quickly.
Enabling Real-Time Business Insights with Edge Computing
Remember, Industry 4.0 isn’t just about IIoT or automated equipment on the production line. It’s also about innovative technologies that can dramatically improve the industrial environment: big-data analytics, machine learning, and artificial intelligence, for example. These new technologies lead to advantages like predictive maintenance and smarter, faster decision-making. The closer to real-time you get your data feeds, the more responsive your business can be.
The trouble is, the further data travels, the slower your digital tools respond. Edge computing—in which data is collected, organized, and processed near its origin point—boosts speed by limiting distance. And speed isn’t the only advantage of placing your IoT database at the edge. An IoT Edge Hub is a new piece of technology that’s becoming more common in Industry 4.0 topologies. An IoT Edge Hub enables different data sources and targets to interact seamlessly, providing robustness and resilience to the communication layer that’s the backbone of this new environment. An edge-based IoT hub can also:
Reduce bandwidth demands
Cut cloud storage costs
Minimize spending on cloud data processing
Do more with a smaller IT footprint
Support digital twins by storing the same data in multiple locations
Ready to get the advantages of Industry 4.0 for your manufacturing facility? It all starts with the right computing infrastructure: an edge IoT hub that supports the MQTT protocol. These systems are the key to IT/OT convergence in manufacturing, effectively removing the final stumbling block to smart factory implementation.