Manufacturing processes are undergoing a major transformation. Now, we’re not talking about part to product with all the gaps in between, but simply product to part, in real-time.
It all started with advancements such as 3D printing, and now of course AI technology is enabling manufacturers, for the first time, to observe their processes in real-time. The real-time element is key to reaping the efficiencies.
Sumeet Puri, chief technology solutions officer at Solace, explains how this groundbreaking shift is enabling manufacturers, their teams and their operations for the first time to function seamlessly and in real-time. And of course, it’s all about the people too!
The evolution of how data is exchanged in manufacturing has been nothing short of transformational, and it’s now nearing its full potential. Looking back to Industry 3.0, the journey began with factories introducing connectivity, where centralized ERP monoliths started linking various parts of the system. At that point, manufacturing was only just beginning to understand and integrate the flow of data.
With the arrival of Industry 4.0, the centralized ERP system evolved into a more modular structure. This marked a pivotal moment in the understanding of data in motion, as Information Technology (IT) and Operational Technology (OT) began to merge and exchange critical information. Systems like Manufacturing Execution Systems (MES), SCADA systems and historical fault detection systems started to connect on the plant floor, further advancing the digital transformation.
Never Forget the Humans!
From this Industry 4.0 foundation we are now moving toward Industry 5.0. A European Commission Policy Brief defines the target of Industry 5.0 to “aim beyond efficiency and productivity as the sole goals, and reinforce the role and contribution of industry to society.” It should complement the existing Industry 4.0 approach by specifically putting research and innovation at the center of the transition to a sustainable, human-centric and resilient manufacturing industry.
North American organizations also see human workers at the core of Industry 5.0 with company growth spearheaded through a combination of innovation and human capital. Alongside this, there are also pressing opportunities to capitalize on AI all while keeping tabs on human centricity, sustainability and resilience. To enable this requires a technical balance to ensure humans and machines work together – each learning from the other.
Achieving this harmony begins at the data level. Industry 5.0 triggers further convergence of IT and OT – aggregating shop floor data in real-time to help bridge the gap; continuously collecting and analyzing data, and offering a comprehensive view of manufacturing operations. This data can then be delivered to enable key stakeholders, especially workers on the factory frontline, to make critical decisions based on accurate, real-time data.
Switching up the Approach to Data Exchange
Imagine a world where business operations are no longer constrained by delays or bottlenecks. This applies not only on the factory floor, but across the rest of the enterprise, and each aspect of the business. What if you could connect everything, even if you were using multiple systems to manage manufacturing in the front and back office?
This could be systems in the OT layer with systems in the IT layer in a secure, guaranteed, throttled, multi-site and cloud, and most importantly, real-time streaming manner. Specifically, this includes operational systems such as MES, programmable logic controllers (PLCs), SCADAs, OPC unified architecture (OPC UA) layers bisectionally connected with master data, product lifecycle management (PLM) systems, customer relationship management (CRMs) and incident management systems from SAP, Salesforce, ServiceNow, Microsoft, Oracle and many others.
Any of these systems can be connected seamlessly with each other across a wide variety of factory, inventory and logistics use cases. To enable this, integration needs to re-invent itself, especially when it must bring in other technologies that are becoming prevalent in factory operations, such as artificial intelligence. For this Industry 5.0 and AI-driven world to happen, we need to think differently.
Here Comes the Manufacturing Event Mesh
Loosen Up
This requires thinking about integration in a much more modern way. We need to stop using a traditional batch historian and update, or an enterprise service bus (ESB) as an architecture, where a centralized software component performs integrations between applications. We need to evolve to a much more loosely coupled event-driven approach to moving data. This is the foundation of Industry 5.0 as far as its enablers are concerned.
As you Sow, so Shall you Reap
One application publishes messages or events, and other applications receive it. Newer applications or devices just come in, as they start to listen to data, new data starts to flow towards them. Adding more and more applications becomes super seamless.
Data Flows
This allows manufacturers to extend this data movement between devices and sensors, so all kinds of sensors can be publishing information or subscribing to information.
Take, for example, a production line going down. This is an event on the OT side of the house. Which customers and what elements of the supply chain are affected can only be determined by correlating this OT event with all those other IT systems – ERP, CRM, transport management, logistics etc. Imagine streaming the event “production line is down” in real time to the IT systems in a one-to-many manner, and the visibility and real-time action this brings.
An Event Mesh is Born
An event mesh is the data fabric which connects systems – IT, OT, AI – effectively as a universal connectivity fabric. It enables us to have many devices integrated together, connecting plants and logistics and then being able to govern all of this, understanding all events in real time.
Real-time is key because events are instantaneous “occurrences” whether on the IT side or OT side. Using an event mesh, we can look astutely at any event and find that they can be depicted as objects + actions + properties using “topic routing.” Take the example of “production line” (object) + “failed” (action) + “in region X, at plant Y, line Z” (properties).
An event mesh routes these occurrences in real time, guaranteed to all applications and systems who are interested and “tuned” in. Applications are natively connected to the event mesh, such as SAP, OPC UA using MQTT, or they connect via micro-integrations, which are lightweight connectors to allow legacy applications to connect to the mesh to produce or consume events.
Putting Tech Down on the Factory Floor
The industrial metaverse, as highlighted by EY, has the potential to revolutionize production floor processes and management optimization. It’s become possible through data-driven digital twins, model simulations and data analytics – paving a path that will transform how work is performed. Nvidia Omniverse is an example of this.
But the metaverse needs to connect to the physical universe in real time. It is cost and energy prohibitive to keep training AI models in real time. So how do we integrate AI with real time data? Agentic AI and Retrieval Augmented Generation (RAG) are being used to integrate GenAI capabilities with real-time data. This real-time data is essentially event streams on the event mesh, flowing into Agents or RAG vector databases, keeping them up to date with real-time context.
Event-driven integration can set up manufacturers to adapt to all these new changes on the factory floor, better capitalize on new technologies such as AI models, or connect to growing industrial metaverse applications in manufacturing. The enabler for AI is an event-driven integration mechanism, providing real time context to AI in autonomous systems, through something called a “context mesh.”
A context mesh brings together the entire context of an enterprise, which can serve as the bedrock of sophisticated AI-based applications – from intelligent assistants using GenAI models and complex analytical tools, to machine language-based recommendation models and purpose-built AI applications using deep or reinforcement learning. This becomes the fabric that pushes that real-time context onto these digital twins.
Industry 5.0 is the Future, and it’s Happening Now – Manufacturing Real-Time Use Cases
Take the example of one leading multinational engineering and technology company that uses event-driven integration to connect its global manufacturing facilities. Specifically, the manufacturer has deployed event brokers in each of its 160 plants, and also in its IT layers on-premise and in the cloud, forming a large interconnected event mesh.
Master Data Management at Scale
With an event mesh, the company has been able to streamline the distribution of huge volumes of product master data across its enterprise.
For instance, its global operations produce 7,000 parts per minute. To achieve this, the company needed to send the production master data, such as a master Bill of Material, to multiple production facilities. This involved sending 6,000,000 messages, equivalent to three terabytes of information per day, to different plants worldwide.
As these products are rolled out to be manufactured at more plants or master data changes, the data requirements become more vast and more complex – creating a huge end-to-end scenario.
But with an event mesh, the manufacturer has been able to confidently share production master data to all of its required environments in real-time. This ability to connect factories around the world is underpinned by a stable asynchronous connection between core data centers around the world and its different plants.
AI Deployment to Minimize Errors
This company has also been able to deploy AI across production lines to concentrate error levels to lower than one part per 10 million produced parts. The company is now looking to speed up production lines with these different models and reduce the error rate.
By relying on an event-driven integration backbone to underpin the data requirements of new AI models, the company aims to further increase its success rate within production lines. In fact, the manufacturer estimates it can scale to minimize errors to one part per 100 million produced parts in the future.
Changing Traditional Methods Into Modern Methods
At its very being, Industry 5.0 relies on human-machine collaboration – and its all powered by real-time data exchange. But, for the manufacturing sector to embrace Industry 5.0, it must extend far beyond traditional integration methods.
It’s where event-driven integration will be a crucial enabler to harness the full potential of real-time data in global manufacturing.
The technology is ready – and humans are taking center stage once again!
