The fourth industrial revolution, referred to as Industry 4.0, is fundamentally transforming the way metal products are manufactured. Intelligent machines, autonomous production lines, cyber-physical systems, and real-time data analytics – all these elements create a new work environment in which the human role is undergoing a profound redefinition. At the center of this transformation stands the operator – a production worker who, for decades, was primarily an executor of physical activities at a lathe, milling machine, or press. Today, they are becoming a supervisor, a diagnostician, and a collaborator of intelligent systems.
This article analyzes how Industry 4.0 changes the operator’s function in the metalworking industry: what competencies are required of them, what technologies they must cooperate with, what challenges production plants face in terms of workforce transformation, and what opportunities this revolution brings for both employees and enterprises.
The term “Industry 4.0” (German: Industrie 4.0) was formalized in Germany around 2011 as a strategic initiative of the federal government aimed at maintaining the competitiveness of the German manufacturing industry. The term describes the fourth great wave of industrialization – after steam-powered mechanization (Industry 1.0), electrification and mass production (Industry 2.0), and automation using electronics and IT (Industry 3.0).
Industry 4.0 is based on several technological pillars:
The metalworking sector – including turning, milling, grinding, drilling, laser cutting, bending, stamping, or welding – is one of the areas where digital transformation brings particularly tangible results. New generation CNC machines are equipped with dozens of sensors monitoring: temperature, vibration, cutting forces, tool wear, and surface quality. This data goes to analytical systems that optimize machining parameters in real-time.
For decades, the machine tool operator – of a lathe, a conventional milling machine, or a press – was primarily a craftsman. Their work required:
This knowledge was largely tacit (tacit knowledge) – passed from master to apprentice, difficult to codify and transfer. The operator worked in close contact with the machine, and their senses were the primary quality control tool.
The concept of “operator 4.0” (Operator 4.0), popularized by researchers such as Romero et al. (2016), describes a production worker equipped with digital tools who acts in synergy with intelligent systems. Operator 4.0 is not only a machine user – they are a process supervisor, a data analyst, and an active participant in the knowledge management system in the plant.
Key types of operator 4.0 in the context of metalworking:
Operator with a decision support system – uses HMI (Human-Machine Interface) interfaces presenting recommendations regarding machining parameters, tool status, and quality forecasts.
Operator-analyst – interprets process data, identifies trends and anomalies, initiates corrective actions before a failure or defects occur.
Operator-robot collaborator – works alongside cobots during assembly, machine loading/unloading, or ergonomically burdensome activities, focusing on tasks requiring situational assessment and dexterity.
Augmented reality operator – uses AR goggles to visualize maintenance instructions overlaid directly on the machine, which shortens changeover and service time.
Remote operator – monitors and manages multiple machine tools or even an entire production hall from a single station, and in the case of machining centers – potentially remotely.
Contemporary machining centers are equipped with new generation CNC controllers (e.g., Siemens SINUMERIK ONE, Fanuc 30i, Heidenhain TNC 7), which not only execute machining programs but actively monitor the process state. The following are available to the operator:
SCADA (Supervisory Control and Data Acquisition) systems allow the operator to view the status of the entire production line on one screen. Trend charts, alarms, OEE (Overall Equipment Effectiveness) indicators – all this information allows them to make informed decisions without having to physically check each machine.
The Industrial Internet of Things (IIoT) means a dense network of sensors mounted on machines and in processes. In the context of metalworking, typical applications are:
Data from sensors is sent to IIoT platforms (e.g., Siemens MindSphere, PTC ThingWorx, Bosch IoT Suite), where it is aggregated and analyzed. The operator sees the results of this analysis in the form of clear dashboards rather than raw rows of numbers.
A digital twin (digital twin) is a virtual replica of a machine, process, or an entire plant, synchronized in real-time with its physical counterpart. In metalworking, it allows to:
For the operator, the digital twin becomes a tool for “sampling” changes before they are implemented physically – a revolutionary change compared to the days when testing a new machining program took place directly on expensive material.
Machine learning algorithms analyze historical data from machines and identify patterns preceding failures or quality degradation. Examples of applications in metalworking:
The operator’s role in this ecosystem is to interpret the AI system’s recommendations, verify them in the context of conditions that the machine does not see (e.g., specific properties of a particular batch of material), and make the final decision.
Cobots (e.g., Universal Robots, FANUC CRX, KUKA LBR iiwa) are industrial robots designed to safely cooperate with humans – without physical barriers, with force sensors reacting to contact. In metalworking, cobots take over:
The operator in such an environment becomes the cobot’s programmer and supervisor, responsible for defining tasks, parameterizing grippers, and monitoring the correctness of operation.
AR systems, such as PTC Vuforia, Scope AR, or Microsoft HoloLens with dedicated industrial applications, provide the operator with information overlaid directly on the field of vision:
Studies indicate that AR systems can shorten the time of performing complex assembly and service activities by up to 30–50%, and the error rate drops dramatically due to eliminating the need to interpret paper instructions.
The transformation of the operator’s role requires a new set of competencies that combines traditional technological knowledge with digital skills. They can be divided into four areas:
Technological competencies (hard):
Analytical competencies:
Soft and adaptive competencies:
Safety competencies:
There is an important debate around the impact of automation on workers. A pessimistic scenario assumes deskilling – the degradation of skills when the machine takes over more and more tasks and the human becomes only an alarm supervisor. An optimistic one points to upskilling – equipping the employee with higher-order competencies that make their work more valuable and satisfying.
In metalworking practice, both phenomena are observed. On the one hand, simple turning or milling operations on standard CNC machines can be increasingly easily automated. On the other hand – handling flexible machining cells, programming cobots, analyzing quality data, or optimizing processes require competencies that were not previously expected of a manual worker.
The key is the active policy of enterprises that invest in the development of employees, not just in machines.
One of the biggest challenges of the Polish and European metal industry is the competency gap (skills gap). Older, experienced operators possess invaluable technological knowledge but often have difficulty adapting to digital interfaces. Younger employees are digitally proficient but lack an understanding of machining processes.
Solutions used by leading plants:
The implementation of Industry 4.0 technology often encounters resistance from employees – fear of layoffs, fear of excessive surveillance (tracking performance in real-time), or simply reluctance to change proven habits.
Effective change management requires:
The Industry 4.0 environment brings new ergonomic challenges. The operator spends more time at screens, which creates a risk of excessive strain on the eyes and the musculoskeletal system. At the same time, physical work with loading or handling heavy elements is taken over by robots and cobots, which reduces the risk of strain injuries.
New threats are:
The implementation of Industry 4.0 in metalworking requires significant infrastructure investments: Wi-Fi or fiber optic industrial network in the hall, edge computing for local data processing, integration of old and new machines (the problem of so-called legacy systems). Operators must be aware of this infrastructure to understand system limitations and respond to possible communication failures.
The traditional operator was assigned to a specific machine. In Industry 4.0, operators manage machining cells (several machines linked by cobots and transport systems) or even entire flexible production lines. This is a fundamental change in work organization.
Instead of a master-foreman-operator hierarchy, a flatter structure appears in which the operator has direct access to data and can – and sometimes must – independently make operational decisions. Autonomy grows, but so does responsibility.
One of the key challenges is ensuring information continuity between shifts. In an Industry 4.0 environment, where process parameters, tool status, and order status are constantly updated in the digital system, “electronic shift handover” replaces traditional notebook communication. The operator finishing the shift leaves their digital footprint in the system – which brings both benefits (full process history) and challenges (privacy, responsibility).
Higher qualifications of operators in the 4.0 environment should translate into higher salaries and new career paths. In leading plants, one observes:
Leading mechanical plants in Germany, Japan, and Scandinavia have been implementing the concept of a smart factory (smart factory) for several years. Typical elements of such a plant in the metalworking industry:
Tool Condition Monitoring (TCM) systems – piezoelectric sensors in tool holders measure cutting forces and transmit data to a predictive system. The operator receives a signal about the need to replace the tool in advance, eliminating breakages and defects.
Automatic in-line quality control – measuring heads mounted directly in the machine tool or at a station between operations perform measurements of key detail dimensions after each cycle. The results are automatically compared with the CAD model, and deviations generate an alarm for the operator.
Flexible cells with cobots – a Universal Robots UR10 cobot handles three CNC lathes, performing loading/unloading, while the operator programs subsequent production orders in the MES system and monitors OEE indicators on a central dashboard.
Polish enterprises from the metalworking sector – especially tier-1 and tier-2 suppliers for automotive and aviation – are intensively investing in Industry 4.0 technologies. Industrial clusters in the Silesian, Lesser Poland, Lower Silesian, and Podkarpackie voivodeships bring together companies implementing both advanced CNC machine tools as well as IIoT systems and cobots.
However, the challenge for the Polish SME sector is the entry price for a full digital transformation. For smaller plants, a gradual implementation strategy is more realistic: starting from machine monitoring (relatively cheap sensors and software), through digitalization of quality control, to full cells with cobots.
With the progress of artificial intelligence and robotics, the question arises: will the role of the operator in metalworking not disappear completely? The analysis allows to distinguish several categories of tasks and their susceptibility to automation:
Tasks easy to automate:
Tasks difficult to automate:
The expert consensus indicates that in the perspective of 10–15 years, the operator will not disappear, but their role will become more cognitive than manual. The number of operators needed to handle the same number of machines will decrease, but the remaining ones will be better paid and perform more valuable work.
Parallel to the discussion about Industry 4.0, the concept of Industry 5.0 appears, promoted by the European Commission since 2021. Industry 5.0 emphasizes three values: human-centric, sustainable, and resilient.
In the context of the operator, this means a return to the central role of the human – not as cheap labor replaced by robots, but as a key participant in the production system whom technology serves, rather than replaces. Ergonomics, worker well-being, ethical supervision of AI – these are the topics of Industry 5.0 that are already shaping a new approach to designing workstations in metalworking.
The transformation of the operator’s role towards the 4.0 model requires a thoughtful strategy from enterprises:
Industry 4.0 is not the end of the operator’s role in metalworking – it is its deep transformation. The human remains at the center of modern production, but their value no longer flows solely from physical strength and resistance to monotony. The operator’s new asset becomes the ability to interpret data, make decisions in complex situations, cooperate with intelligent machines, and continuously learn.
It is a difficult transformation – it requires effort from employees, significant investments from enterprises, and systemic support from education and industrial policy. But it also brings deeper benefits: safer workstations, higher qualifications and salaries, less waste of materials and energy, and higher product quality.
The operator 4.0 in the metalworking industry is not a human replaced by a machine – it is a human strengthened by technology, capable of performing work that for decades exceeded the capabilities of both humans and machines acting separately. It is precisely this synergy that is the promise of Industry 4.0 – and a challenge that the metalworking industry must meet.