The first part of this paper discusses the research context, taking a closer look at the development of Industry 4.0 and the growing importance of the IIoT, which entails new cybersecurity challenges. The issue of cyber threats and the need to increase the level of protection in machine control systems, which are particularly vulnerable to attacks due to their connection to the network, is also presented. The Introduction concludes with a presentation of the article’s objective, which is to analyze the requirements of security levels (SLs) and the implementation of relevant international standards. The next section reviews the current research on cybersecurity in machine control systems. This section also points out the research gaps that the article aims to fill. The next section presents the risk assessment used to ensure safety during machine operations based on ISO 12100. The article describes safety functions implemented in machine control systems, including the SIL (safety integrity level) and PL (performance level) specifications. An important part of the article is the creation of a relationship between PL and SL, showing how the safety functions of systems are related to protection against cyber threats. The last part of the article gives a case study in the form of examples of machines and their control systems performing safety functions, which require various SLs depending on the PLs.

The article discusses the construction and functionality of a modular line for the production of low-emission composite fuel, which was developed as part of a project co-financed by European Funds, the aim of which was to develop an ecological, composite solid fuel intended for low and medium power boilers. The designed and built innovative production line has been tested in terms of safety requirements in accordance with the Machinery Directive 2006/42/EC. Based on the harmonized standards, the risk estimation algorithm was selected. The assessment covered, inter alia, mechanical, electrical and thermal hazards, hazards related to noise and processed material, and those related to control systems that perform safety functions. In order to eliminate non-conformities, technical and organizational measures increasing the safety of service were proposed.

The article focuses on the description of non-conformities occurring in safety-related control systems of machines collected by the author during safety audits of machines and production lines. The aim of the article is to familiarise machine designers with safety requirements and ways of eliminating common mistakes made during design, while at the same time indicating to investors buying machines which requirements to take into account when placing an order.

This article presents the potential for maliciously influencing a control system by interfering with the program code of an industrial controller, using a temperature control system for a heating process based on resistive electric heating as an example. The presented attack scenarios are crucial for the energy efficiency of electric heating systems, which is related to the issue of cybersecurity in the area of energy security. The aim of this research was to demonstrate that a cyberattack involving the malicious manipulation of the setpoint can be carried out in a manner invisible to the heating process operator and be difficult to detect using classical time-domain control quality indicators (time-response specifications). The first involves incorporating proportional elements with mutually inverted gains into the input and output of a closed-loop system. The second method is based on adding an additional transfer function G_m(s) in parallel to the control system. The difference between the correct and manipulated setpoints is introduced into the input, and the output signal is added to the actual (hidden) value of the controlled variable. In the first method, at the moment of starting the control system, there is a difference between the apparent (falsified) value and the ambient temperature. In the second method, the inclusion of an additional G_m(s) ensures that the apparent (falsified) value of the controlled variable matches the temperature at the moment of starting the system. PID control enables achieving satisfactory control quality in heating processes, which are characterized by high inertia and time delays. Compared to classical PID regulation, advanced control methods can, under certain conditions, provide better performance in terms of quality indicators. However, due to their high computational complexity and sensitivity to model uncertainty—particularly in methods relying on accurate system identification—PID controllers continue to be widely used in industrial practice. For this reason, the present study focuses on a control system based on a PID controller as a practical solution. Based on the results, it was found that the most effective manipulation occurred within the range from 0.9 to 1.1 of the actual setpoint value for both the first and second method, using a model with $T_m$ between 5 s and 30 s. In these cases, the quality indicators referenced to the nominal values, determined for the falsified control system responses to a step change in the setpoint, were as follows: overshoot—0.97 and 1.30 (method 1), and 0.90 and 1.10 (method 2 for 5 s), 0.75 and 1.30 (method 2 for 30 s); settling time—1.06 (method 1), and 0.98 and 1.17 (method 2 for 5 s), 0.85 and 1.14 (method 2 for 30 s). The settling times determined for the system’s response to a disturbance were: 1.00 and 1.15 (method 1), and 1.13 and 1.16 (method 2 for 5 s), 1.12 and 1.02 (method 2 for 30 s). Based on the conducted analysis, it was demonstrated that the relatively simple setpoint manipulation methods presented can effectively mask the impact of malicious interference on the temperature value in the control system of a heating process.