The digital economy of today is built on open source software. It's what makes cloud platforms, enterprise applications, consumer apps, and almost every other layer in between possible. However, open source is still not widely used in manufacturing, where hardware and software systems work together. That hole is now being filled with new ways of building infrastructure that are designed to meet the needs of industrial environments.
Why Manufacturing Needs a New Software Stack
Most digital manufacturing initiatives fail not for a lack of ambition, but because the foundational infrastructure isn't ready. Connecting shop floor assets to analytics platforms is not a straightforward process. It involves dealing with legacy equipment, unreliable network conditions, incompatible data formats, and the requirement for edge processing.
Even platforms that have been around for a long time don't always work. Many promise to work from start to finish, but they fail when it comes to the real-world task of connecting dozens of machines with different interfaces. Tools may need to change protocols, store data locally when the internet goes down, or have extra databases to handle temporary storage. These are not unusual situations in industrial settings.
Factories are data-intensive environments. Machines, ranging from programmable logic controllers (PLCs) to environmental sensors, constantly generate valuable data. This data could be used to power real-time dashboards, advanced analytics, AI-powered automation, and even basic performance monitoring. Despite the abundance of raw input, the data frequently fails to reach the applications that require it.
The core challenge is fragmentation. Operational data exists in many formats, lives across various protocols, and is often locked inside proprietary systems. While cloud-native tools and industrial IoT platforms have promised seamless integration, real-world deployments frequently run into limitations, both technical and architectural.
What’s missing is a scalable, resilient layer that connects operational data to modern applications. A middle layer that acts as a unified namespace across the factory ecosystem.
Toward a Standardized, Scalable Architecture
The solution lies in technology built specifically for manufacturing use cases, with open source at its core. A middle layer built on open standards can collect, transform, and route factory data with consistency. It can handle edge processing, lossless data transmission, and output formats that are compatible with cloud-native applications.
Such a stack allows for a unified namespace that serves as a single source of truth for data across machines, lines, and sites. It also makes deployment easier. For example, instead of manually configuring 20 different edge devices, operators can use tools that automate provisioning, enforce version control, and provide built-in monitoring and alerting.
This shift is critical for agility, as factories are under increasing pressure to adapt, whether through new product lines or increased efficiency, the ability to quickly modify or expand infrastructure becomes a strategic advantage.
Why Open Source Is the Rational Choice for Industrial Connectivity
Early digital transformation efforts in manufacturing frequently reveal an uncomfortable truth, and that’s that the tooling available to connect shop floor assets is often both inadequate and expensive. While proprietary edge devices and protocol converters promise plug-and-play functionality, they frequently fail to deliver on flexibility, documentation, and implementation speed. Worse, they carry significant markups, especially when labeled as "industrial grade."
This premium pricing, which is frequently justified by certifications or enclosure ratings, is not always associated with product quality. In many cases, open source alternatives outperform their commercial counterparts in terms of not only capabilities, but also deployment speed and community support. Waiting weeks for industrial hardware or ambiguous PDF-based documentation is vastly different from joining an open-source forum, watching a how-to video, or troubleshooting problems with a global community, often in real time.
For teams under pressure to deliver and iterate quickly, open source becomes the pragmatic default. It provides flexibility, codebase visibility, and a vibrant ecosystem of tools for common manufacturing problems ranging from protocol conversion to data buffering and visualization.
The Gap Between IT Innovation and OT Conservatism
Despite these advantages, open source adoption in manufacturing remains surprisingly low. In fields like software engineering, DevOps, or even embedded systems, open source tools are ubiquitous. In manufacturing operations, the penetration is closer to a rounding error. This is mostly a result of how systems in operations technology (OT) have traditionally been designed.
IT infrastructure evolves rapidly to meet demands for scalability, performance, and user experience. In contrast, OT systems are built for longevity and stability. A factory value stream might be expected to run continuously for years, if not decades, with minimal interference. This culture of reliability, while understandable, often leads to a reluctance to change, especially at the infrastructure level.
But the notion that industrial infrastructure remains static for decades is becoming less accurate. Reconfigurations, product changes, and shifting demand are shortening the lifecycle of many manufacturing lines. What’s more, clinging to legacy infrastructure under the guise of safety or certification often becomes a roadblock to innovation and a vulnerability in itself.
Breaking Out of the Legacy Trap
Many industrial systems still use outdated operating systems, such as Windows XP, because those configurations were once validated and certified. As a result, they stay frozen in time. In theory, this promotes operational reliability but in practice, it confines organizations to brittle systems, exposes them to security risks, and renders integration with modern tools nearly impossible.
The widespread fear of connecting these systems to the internet, which stems from legitimate cybersecurity concerns, stifles modernization even further. However, isolating infrastructure is not a sustainable strategy. To promote continuous improvement, factories must find new ways to evolve their architecture while maintaining safety and control.
Open source infrastructure provides a path forward as it enables manufacturing teams to standardize integration patterns, strengthen security protocols, and gradually modernize, all without relying on obscure or inflexible vendor stacks.
Rethinking the Industrial Data Architecture
Unified Namespace (UNS) is a concept gaining traction among control engineers, system integrators, and architects. It’s an event-driven manufacturing architecture designed for real-time data flow across all levels of the organization.
In many IT systems, this approach is already standard. Data streaming platforms like Kafka sit at the center of logistics, R&D, and customer platforms, moving data efficiently and securely. The Unified Namespace simply applies this proven concept to manufacturing, making it more accessible and tangible for industrial environments.
It reflects best practices from modern IT infrastructure brought into the OT domain, where they can provide measurable value, faster decision-making, simplified integration, and better visibility from the shop floor to the C-suite.
Unified Namespace decouples applications from infrastructure. You no longer need to buy your PLC, SCADA, and visualization tools from the same vendor. Applications become interchangeable, composable, and swappable without breaking the entire system.
It also enables a kind of plug-and-play architecture for the industrial world. Once data is flowing in real time through a common namespace, new systems can be added or removed with minimal disruption.
At the heart of the Unified Namespace is a messaging pattern called the publish-subscribe (pub/sub) model. A “publisher” sends out updates, and anyone who’s interested (a “subscriber”) receives them, instantly and automatically.
In an industrial context, this means that a sensor publishing temperature data doesn’t need to know who’s listening. It just emits data. Any application like a dashboard, an alerting system, or a cloud analytics engine can subscribe to that stream and act on it.
This model reduces complexity, eliminates brittle point-to-point integrations, and enables real-time responsiveness across systems. It’s a well-established pattern in IT, and it’s finally becoming accessible to OT teams, thanks to technologies like MQTT, Kafka, etc.
Building the Knowledge Base First
Before any of this transformation can happen, teams need a shared vocabulary. Misunderstandings around terms like “real-time,” “streaming,” or even “database” can derail progress before it starts.
The Unified Namespace can act as a bridge between IT and OT only if both sides speak the same language. When operations engineers understand the principles behind pub/sub or data streaming, they gain the power to push back when IT blocks innovation. When IT understands the constraints of shop floor equipment, it can design architectures that work in the real world.
This shared foundation is what unlocks faster innovation, safer deployments, and cheaper experimentation.
Five Open-Source Concepts Every Operations Team Should Learn
For those just beginning this journey, there are a handful of technologies and concepts that provide enormous leverage. Here are five critical areas to understand:
Networking Fundamentals: Learn how devices communicate, not just cables and IP addresses, but protocols like TCP and UDP, and how they impact reliability and latency. This is the foundation for understanding any distributed system.
Databases and Their Types: Understand the difference between transactional (OLTP) databases, like SQL, and analytical (OLAP) platforms like Snowflake. Know when to use each, and what queries they’re optimized for.
Message Brokers: Explore tools like MQTT and Kafka to understand how data can flow through systems without direct point-to-point connections. These are the backbone of modern, flexible manufacturing platforms.
Flow-Based Programming: Tools like Node-RED provide low-code environments to build and test logic at the edge. They’re ideal for rapid prototyping, integration, and even production workloads in some scenarios.
Dashboards and Visualization: Platforms like Grafana make it easy to create dashboards from real-time or historical data. Understanding how to connect a broker to a time-series database and visualize it is an essential skill in a data-driven environment.
Future-Proofing Industrial Architectures
As manufacturers adopt these patterns, there are basically preparing for tomorrow’s problems. The rise of open protocols, cloud-native thinking, and flexible architectures gives them the power to evolve without starting over.
From Linux to Kubernetes, Grafana to MQTT, the infrastructure that once powered backend IT systems is now powering shop floors and assembly lines.
Manufacturers no longer want a one-size-fits-all stack, they want the freedom to mix and match specialized tools, like for example custom schedulers for AI-driven optimization, and open standards to connect everything.
This flexibility is a departure from how industrial systems were historically designed, where the architecture often dictated business options. Today, business needs define the architecture and open, modular systems make that possible.
How Solwey Can Help your Business
At Solwey, we help manufacturers streamline operations, reduce inefficiencies, and make smarter, faster decisions through custom software solutions built specifically for the manufacturing sector. Whether you're dealing with complex supply chains, production line bottlenecks, or outdated legacy systems, we create tools that align with your workflow and scale with your business.
Unify production, inventory, and operational data into one centralized dashboard, so your team doesn’t have to juggle disconnected systems. Monitor KPIs across facilities, identify inefficiencies, and allocate resources with precision. Our AI-powered insights surface trends and recommend next steps, helping you minimize downtime and maximize output.
We understand the pressures of modern manufacturing and that’s why our agile development process gets solutions into your hands faster, without compromising quality. And with Solwey, you don’t have to choose between premium service and affordable pricing, you get both.
Let Solwey be your technology partner in driving operational excellence. Contact us today to start building smarter systems for your shop floor and beyond.
