In 2025, that revolution is still very much underway. Many manufacturing companies are working hard to realise this vision. Digital progress usually doesn’t come from one big leap, but from many consecutive small steps. For example, by adding a sensor to a machine or implementing a system that automatically records data. Such improvements may seem small but immediately deliver greater insight, higher efficiency, and better quality—benefiting both companies and their customers.
Each step lays the foundation for the next. In this way, organisations gradually grow towards a future in which processes are smarter, faster, and better integrated. That is the essence of Industrie 4.0, also known as Smart Industry in the Netherlands. The Fourth Industrial Revolution builds on three earlier turning points: From the mechanical loom (1764), to the first electric power plant (1882), to Programmable Logic Controller (PLC)-driven machines (1968). To define this development, Smart Industry distinguishes six maturity levels. These levels help organisations determine where they currently stand in their digital journey and which steps are needed to move forward.
The six maturity levels of Smart Industry are:
- Smart components
- Smart machines
- Smart factories
- Connected factories
- Intelligent organisations
- Autonomous organisations
1. Smart Components
Smart components form the foundation for all subsequent levels. The first step towards a smart factory is adding sensors, actuators, and connectivity to individual components so they can collect and transmit data to central systems. In a factory using smart components, for example, every container of parts is equipped with an RFID tag. When the container is nearly empty, the warehouse automatically receives a replenishment signal. Technologies such as IoT sensors and basic SCADA systems play a key role in collecting and visualising this data.
2. Smart Machines
A machine becomes ‘smart’ when it combines multiple digital components and can alert operators to deviations or wear. Maintenance becomes more efficient, and this is the first step towards a full digital twin. An example of a smart machine is a milling machine equipped with vibration sensors that can predict when a cutting tool needs replacing. Manufacturing Execution Systems (MES) become increasingly relevant at this level. They collect real-time data from machines and support work preparation and production control. Robotics may also be introduced for repetitive tasks, reducing the risk of human error.
3. Smart Factories
In the next phase, the entire factory becomes digitally connected. All processes can be monitored and controlled in real time from central systems. Using an MES, the Enterprise Resource Planning (ERP) system and the machines are linked. This ensures that production planning is optimally aligned with inventory, orders, and capacity. For instance, an automotive parts manufacturer can use sensors on production lines, Computer Numerical Control (CNC) machines, and assembly stations to monitor and adjust production in real time. Deviations in parts can be detected immediately, production volumes can be adjusted, and quality checks can be automatically triggered.
4. Connected Factories
Once individual factories are fully digitised, the next step is connecting multiple sites and supply chain partners. Data is shared and processes are automatically synchronised. Production capacity, raw materials, and deliveries are efficiently planned within a data-driven ecosystem. MES and ERP systems play a crucial role in coordination, while AI algorithms predict where and when production should be shifted to avoid disruptions or shortages. At this point, for example, production from one factory can be automatically redistributed to others in the event of a failure.
5. Intelligent Organisations
The next level brings together all data generated across the organisation. With the help of BI and AI analytics, strategic decisions are supported by data. Organisations gain greater flexibility, reduce time-to-market, and can respond more rapidly and precisely to customer needs. For example, AI can predict an upcoming price increase for certain components, prompting the organisation to automatically stock up while prices are still favourable. MES and ERP systems continue to supply operational data, while advanced analytics support process optimisation and strategic planning.
6. Autonomous Organisations
The highest level of Smart Industry is an organisation capable of largely steering itself autonomously. Automated process optimisation and autonomous supply chains minimise human intervention. In a fully autonomous enterprise, orders are automatically read and scheduled based on delivery commitments. Robots prepare the work, assemble the products, and place them in packaging stations, after which the system automatically generates shipping labels and handles logistics.
A prime example of a factory approaching this highest level of Smart Industry is FANUC in Japan. FANUC produces industrial robots, CNC control systems, and automation components—and uses its own technology in its manufacturing process. In this so-called “lights-out factory”, robot cells operate entirely independently: They machine components, assemble robots, transport parts, and handle packaging. Orders are automatically processed, and machines adjust themselves according to specific production requirements. The result is a factory that operates largely autonomously, with only minimal human involvement for maintenance and quality control.
Smart industry is not just about technology
The highest level of Smart Industry is not only about technology. It is about combining innovation with organisational and cultural change. Organisations must not only integrate technology into their systems but also embrace data-driven decision-making, train employees, and align business models with this new way of working. When these elements come together effectively, a new future perspective emerges—often referred to as Industry 5.0: a phase in which smart systems and humans collaborate, making complex tasks easier, enabling mass customisation, and driving further innovation.
The road to a future-ready factory
For many medium-sized manufacturing companies, smart machines, connected factories, and fully data-driven organisations are not yet part of daily reality. That doesn’t mean nothing is happening—the first steps are often already taken. Think of sensors on machines, digital recording of production processes, or the use of an MES system to collect data and gain insight into the production line.
By expanding these applications step by step and capturing them in a clear digitalisation roadmap, companies can work purposefully towards smart components, connected processes, and data-driven decision-making. In this way, even a medium-sized factory can achieve significant efficiency and quality gains while building a solid foundation for a production environment that becomes ever smarter and more future-proof.
