Industrial revolutions change the world. The factories, foundries, and facilities that churn tirelessly are the engines of our entire civilization. Chemical plants, production labs, oil refineries, construction sites, assembly lines. The great endeavor of human creativity on a massive scale, wrought in steel and smoke and, in Industry 4.0, silicon.

Computerized Factories

Computers play a central role in the modern industrial environment. These cyber-physical systems now govern everything that happens on the site floor. Sensors that collect data on temperature, air pressure, vibration, humidity, motion, and much more. Predictive maintenance on sensitive equipment. Machine learning algorithms that monitor processes for accuracy and error reduction. Supply chain configuration, energy management. All data that is essential to operations and the health of the overall business or national concern.

As such, everything on the factory floor is a smart device now - everything from helmets to forklifts - that integrate with the manufacturing process. Cameras to monitor labour activity. Robotic arms that attach car doors. Barcode scanners, conveyor belts, storage units - and every other device on the factory floor. All are now devices within the Industrial Internet of Things (IIoT). All of them are constantly querying, processing, reacting to, and transmitting data about operations on the factory floor to help the art of making things run smoother, faster, and more efficiently than ever before. 

Data On the Factory Floor

And, with automation only going to increase, this computational data web that manages the factory environment will only get more complex. Even human labour will be augmented with VR headsets that provide augmented reality feeds to exponentiate their productivity. Manufacturing will continue to get smarter and more interconnected, with the ability for multi-site configurations to work off the same data sets and adjust their behaviour accordingly. 

To get really smart, however - to absolutely maximise the efficiency of these industrial processes - the IIoT needs Edge Compute capabilities. When it comes to advanced manufacturing - milliseconds matter. It’s a millisecond that is the difference between the creation of a successful transistor chip or junk metal, a car that drives and a car that’s scrap, a reactor critically overheating or switching off successfully in an emergency. Nowhere more than the factory floor do these latency concerns matter. 

Why Cloud Latency Undermines Manufacturing Processes

The factory floor can’t rely on the cloud for operations, it can’t be exposed to the downtime risks. An app not working because a server is down is a problem. Safety systems not coming online because a server is down is a catastrophe. The Local-First computing paradigm is essential for Industry 4.0 to be a truly world-changing revolution, and distributed data management like the one provided by Source Network through its stack is critical for optimising processes in industrial manufacturing fleets and making them the best they can be. IIoT-powered workflow automation depends on fast decision making, and Local Edge lets these on-floor devices talk to each other directly and bypass cloud delays.

For example, conveyor belts on assembly lines can dynamically adjust their belt speeds based on the part availability coming down the chute. A robot arm can use real-time sensor data to self-correct with zero latency. Fleets of autonomous warehouse robots can process their navigation data as they move around the factory floor and communicate about one another’s work flows in real time. For developers, edge compute lets them write software that processes data on-site, reducing delays in predictive maintenance and emergency shutdowns. It lets them track pressure and airflow around HVAC systems to adjust to the environment automatically. Inventory management can also be processed locally, and that data then fed through to the rest of the devices in the factory to act accordingly.

This lack of reliance on the cloud also increases the scalability of operations both intra and inter site. A shipping port, for example, that is reliant on a cloud service may find itself paying enormous fees to their server provider to manage the huge amounts of inventory, regulatory, and transport data flowing through their hub. Yet, by adopting edge compute, the hardware investment they’ve already made can carry that burden. This is true for all industrial environments. One-time hardware investments also become the backbone and substrate of their data management operations - while also elevating production processes. Furthermore, they are far more scalable. To boost operations, one need only add more devices to the fleet, with no additional bandwidth demands clogging central servers, increasing operational cost and affecting performance.

Removing Catastrophic Downtime Risk

Breaking reliance on the cloud for the IIoT also removes catastrophic downtime risk. As we mentioned, it’s in sensitive, expensive, or dangerous manufacturing processes that this matters most. Chemical plants can monitor gas leaks locally and trigger shutdowns even if the internet isn’t working. Mining equipment can detect structural instability and give alerts or just switch themselves off before the worst happens. Milliseconds matter. Seconds, or even days, caused by cloud server outages matter even more. This kind of utility saves money and saves lives. 

Of course, many factories often run their own repurposed servers to act as a backup for this purpose. Edge devices often don’t have enough storage or horsepower to manage the entire industrial workload. These servers can integrate with their edge device network to help alleviate the burden - such as assisting with training AI models that can then be repropagated to the devices. With local-first software, every device in the manufacturing fleet, including the backup servers, can share the data burden and operate independently of centralised failsafes and increase redundancy, and deliver on many small operational tasks - such as crucial safety measures, independently.

New Functionality with Edge AI

Local processing also unlocks new functionality, particularly with the incorporation of Edge AI models that can operate on data on device thanks to DefraDB’s distributed data management. A smart grid can process the power load data locally and adjust to meet demand in real time, or a solar farm can use Edge AI to adjust the panels to face the warmth of the sun. Factory owners will be able to train their own models on their factory data - much of which is valuable, proprietary, and fundamental to their competitive edge - without having to store it on a cloud server or give it to a third party model to analyse. By locally deploying on their own hardware fleets, they can massively boost their security.

Secure Environments

Speaking of security. All companies are aware of how valuable factory data is. A chip manufacturer’s factory environment is a closely guarded secret at a national security level. Yet the same is true for factories right down the industrial supply chain. Corporate espionage is a real thing, and reliance on cloud servers only increases the attack vectors and surface threat level. Local Edge means sensitive operational data is kept on-premises, and devices in the fleet can authenticate and act on data without exposing it to a potential wider audience. Even within the device fleet itself, Source Networks’ fine grained ACPs and trust auditing mean the machines only work with the data they need to get the job done. Privacy is not just for individuals, but for corporations too as they compete to become industrial powerhouses.

How Source Network Is the Next Industrial Revolution

Source Network’s tools unlock this Local Edge paradigm for industrial processes. One key aspect of our stack is the way it makes data interoperable and manageable between different device schemas and the type of data they produce. LensVM helps transform the data coming from robotic arms and conveyor belts - which may be made by different manufacturers and operating in different software environments - and unify it so it can be queried and processed under one holistic data management paradigm. By homogenizing application data across disparate fleets and unifying it on DefraDB, that data can then be further used for optimisation on the factory floor. DefraDB seamlessly replicates across every device and helps process and query the data so that they can both use and react to it. Data held on on-premises data servers or in the cloud is still essential, of course. Our distributed data stack is not monolithic, and is built to integrate seamlessly with current traditional architectures.

Our stack also helps build resilience. The security provided by Orbis Secrets Management isn’t just for individuals and their access, but for devices and their access too. Through Source Network, device fleets can be set up in appropriate relational data webs amongst one another so that they can operate at peak efficiency and minimum bandwidth while also getting the data they need to perform their task. 

It also increases resilience and promotes better hardware redundancy when things can and do inevitably go wrong. Should failure happen, SourceHub’s trust auditing means every machine action, sensor reading and system update is immutably recorded and can be traced back to where the failure occurred, as well as being able to restore from disaster back to proper operational states, with the advantage of multiple copies of operational data existing across the devices in the network. 

Compliance in industrial environments is also essential - for example, a pharmaceutical plant needs stringent controls on the data it's both using and the environment its drugs are produced in. SourceHub and DefraDB combine to create provable compliance and pristine data trails through the lifecycle so these sensitive processes can remain compliant - no matter where they are in the world. And, because it's replicable across devices, this whole functionality hyper scales at a rate that’s never been possible before.

The world is building, and what we’re building at Source Network helps everyone build better than ever before. Industrial manufacturing processes are no longer powered by laborers with sandwiches, but by computers. Our distributed data management stack promotes powerful synergies right across device manufacturing fleets that will kickstart the next industrial revolution. Through Source Network, every robot arm, conveyor belt, smart hat, AR headset, camera and sensor on the factory floor can be connected like never before, helping us build better than we ever thought possible.