Manufacturing is facing a complex challenge. Machines and production systems must continue to guarantee the reliability, availability and long lifecycles industry has always demanded. At the same time, manufacturers need greater adaptability: deploying new functionality faster, integrating different systems, making better use of data and responding to changing production requirements.
This is the context in which the Software-Defined Factory (SDF) is emerging.
It does not mean replacing industrial hardware with software. Sensors, controllers, HMIs, industrial PCs and edge devices remain essential to physical processes. What is changing is where intelligence resides and how tightly functionality needs to remain bound to the hardware executing it.
Software-defined automation introduces a different approach: more functions can be configured, deployed, updated and managed through software, allowing hardware and applications to evolve at different speeds.
Traditional industrial automation has largely been built around dedicated hardware, proprietary environments and tightly coupled functions. This model has delivered exceptional reliability, but its limitations become more visible as manufacturers manage heterogeneous production lines, legacy equipment, IT applications, cloud services and growing numbers of connected assets.
Adding functionality may require hardware changes. Integrating technologies from different vendors can become a significant engineering project. Updating applications across large fleets of machines can require considerable time and resources.
The software-defined approach introduces concepts already familiar in IT — modular software, virtualization, containerization, APIs and centralized application management — into industrial architectures.
The objective is not to replace what already works. It is to make automation easier to evolve.
Connectivity and interoperability are the starting point. Standards such as OPC UA and MQTT, together with APIs, allow PLCs, HMIs, sensors, enterprise systems and applications to exchange information. But connectivity itself is increasingly becoming a prerequisite rather than the final objective. The real value lies in what can be built on top of it.
Edge computing is particularly important because it brings computing resources close to machines and processes. Data can be processed locally and applications can operate without depending continuously on the cloud. At the same time, the edge creates a meeting point between OT and modern software architectures, where modular or containerized applications can coexist with industrial protocols and machine-level systems.
The industrial cloud adds scalability. Fleet management, analytics, remote monitoring and software services can extend across machines and production sites. In practice, however, the Software-Defined Factory is not necessarily cloud-first. An edge-to-cloud architecture can keep latency-sensitive or critical functions close to the process while using the cloud where centralized management and computing resources provide greater value.
IIoT platforms connect these layers, acquiring and contextualizing industrial data, managing distributed devices and integrating applications. This is particularly relevant for industrial digital transformation because most companies cannot simply replace their installed base. New capabilities need to coexist with existing assets.
Finally, low-code frameworks, reusable components and standardized interfaces can reduce custom development and accelerate deployment. For OEMs, this means potentially reusing the same technological foundation across different machine families; for manufacturers, adapting applications and workflows more quickly as requirements change.
Making data available is only the beginning. Once information is contextualized, it can become part of operational decision-making.
OEE, downtime, energy consumption, maintenance, quality and production performance no longer need to remain separate information silos. Connecting these dimensions can provide a clearer understanding of what is happening and why.
This is where Smart Manufacturing moves beyond dashboards. The objective is to turn information into action: identifying a loss, understanding its cause, defining corrective actions and measuring their impact.
For manufacturers, this can mean greater flexibility, easier scalability and more effective lifecycle management. For OEMs, reusable software components and more modular architectures can reduce engineering complexity, accelerate customization and create opportunities for new digital services.
Remote diagnostics, centralized software management and updates can also simplify maintenance and contribute to reducing the Total Cost of Ownership over the system lifecycle.
Perhaps the most strategic benefit, however, is the ability to respond to requirements that do not yet exist. When technologies, regulations and manufacturing models evolve rapidly, adaptability itself becomes an architectural requirement.
The convergence of IT and OT is one of the main forces behind the Software-Defined Factory.
Historically, IT and OT evolved according to different priorities. IT focused on scalability, interoperability and rapid software evolution. OT focused on availability, deterministic behavior, safety and continuity of production.
Modern industrial architectures increasingly need both.
An edge application may use technologies originating in IT while still operating according to industrial requirements. A cloud platform may manage information from hundreds of machines, but it must interact with OT protocols, equipment and operational constraints.
The challenge is therefore to bring the flexibility of software into industrial environments without sacrificing the robustness required by physical processes.
This is also why open platforms and interoperability become strategically important. As intelligence is distributed between machine, edge and cloud, isolated technological silos become increasingly difficult to sustain.
For EXOR International and Corvina, the Software-Defined Factory represents a technological direction in which industrial hardware and software increasingly evolve as parts of the same architecture.
At machine level, EXOR HMIs, industrial PCs and edge devices provide computing resources and interaction with the physical process. JMobile provides the framework for visualization and operator interaction, while XPLC extends this architecture towards integrated software-based control.
At the edge and beyond, Corvina technologies extend this continuity towards secure connectivity, remote management, IIoT and Smart Manufacturing applications.
The relevant point is not the number of technologies involved, but the possibility of creating a continuum from machine to edge to cloud, where control, visualization, data and applications can become progressively more integrated while retaining the flexibility to evolve independently where appropriate.
This is also an area of active exploration. The use cases presented by EXOR International together with NXP at CES 2026 investigated concepts related to software-defined automation and how industrial architectures could progressively become more configurable through software.
The distinction matters: the Software-Defined Factory is a concrete technological direction, but one that is still evolving. Not every industrial function can — or should — be virtualized. Determinism, cybersecurity, functional safety, availability and hardware reliability remain fundamental engineering requirements.
The Software-Defined Factory is not the end of traditional automation. It is its evolution.
Industrial hardware, real-time control and OT systems will remain fundamental. What changes is the ability to separate their lifecycle from the growing number of software capabilities built around them.
The factory of the future may therefore not be defined by entirely new machines, but by architectures that can change without being rebuilt every time requirements evolve.
This may be the most practical meaning of software-defined automation: moving from predominantly static automation infrastructures towards industrial platforms capable of continuous evolution.
The future of industrial automation is not about replacing hardware with software. It is about using software to make industrial technology more adaptable, scalable and ready for what comes next.