Częstochowa University of Technology

The study refers to a comprehensive analysis of the occurrence of defects in forgings constituting elements of window fittings, for which, in the process of their production through precision die forging in a six-impression system at elevated temperatures on a hydraulic hammer, we observe bending of the whole forged element and tilting of the stem (a conical element protruding in a plane perpendicular to the main axis of the forging) in the particular forgings. The investigations included analysis of the technology of precision forging on a hydraulic hammer with an energy of 16 kJ, advanced numerical simulations of the process with the use of a calculation package Forge 3.0 NxT, and dynamic tests of mutual displacement of tools performed by means of a high-speed measurement camera. Preliminary analysis of the process showed that, for forgings with a narrowed dimensional and shape tolerance, produced dynamically on a hammer, the key role is played by elastic deformations as well as the construction of the dies and the geometry of the working impressions, and also the changing tribological conditions. For this reason, multi-variant numerical simulations, including two variants of tools (the standard process and the so-called broken perpendicular flash), were carried out, which made it possible to determine the temperature and forging force distribution in the tools as well as the correctness of the deformed forging material’s flow, the filling of the working impressions, and the defects in the forgings. Next, with the use of a high-speed camera, measurements of the relative displacement of the dies were performed, which showed that a proper change in the construction (geometry) of the tools and the use of locks positively affects the minimization of the displacements and thus increases the quality and dimensional and shape precision. The proposed approach using numerical simulations and dynamic measurements of displacements allows for a relatively quick analysis and the introduction of necessary changes in the technology, including modifications of the construction and geometry, in order to minimize the forging defects. That said, the obtained results did not unequivocally point to one specific optimal solution; therefore, the issue of a total elimination of forging defects is still open and constitutes a scientific challenge. And so, further research and verification studies are required to improve the current forging technology and eliminate forging defects in multiple systems in longer operational periods.

Overloaded trucks have a significant impact on road surface degradation, leading to premature damage to infrastructure. Reducing the number of overloaded trucks can help decrease the extent of this damage, which, in turn, will result in less frequent need for repairs and lower road maintenance costs. These conclusions suggest that effective control of vehicle weight is a key element in strategies aimed at maintaining the durability of road infrastructure and optimizing spending on its upkeep. To this end, calculations of potential savings on periodic maintenance as a result of implementing the WIM system were carried out, based on literature assumptions. The results obtained showed that the implementation of a more efficient heavy vehicle weighing inspection system can significantly contribute to reducing road repair costs as a result of a reduction in the share of these vehicles in traffic.

For each market participant, knowing the value of the assets they manage is very important. Real estate is an essential group of such assets. Knowing their value determines the economic efficiency of decisions made on the real estate market. Real estate valuation is complex because the market is not transparent and is characterised by low information efficiency. The study hypothesised that it is possible to model risk in the real estate valuation process. The aim of the article is to identify and describe the areas and sources of risk occurring in Polish valuation practice. A mixed research approach was used: literature research, questionnaire research and qualitative inference methods.

This study explored the role of Circular Economy (CE) strategies in small and medium-sized enterprises (SMEs), with a particular focus on integrating Artificial Intelligence (AI) to optimize CE performance. The research aimed to identify the key determinants influencing CE indicators by using Principal Component Analysis (PCA) and regression modeling. The findings revealed that factors such as employment in CE sectors, resource productivity, and effective waste management practices significantly impact circularity outcomes. These factors were found to be crucial for SMEs striving to enhance sustainability and reduce environmental impact through circular economy practices. The study primarily focused on general Circular Economy strategies, meaning the results may vary across different industries, particularly those with varying waste streams and resource challenges. For instance, certain sectors might face specific hurdles in waste management or resource efficiency, making the application of CE strategies more complex. Additionally, the study uncovered the complexity of systemic interactions within CE implementation, such as the negative correlation between municipal recycling rates and circular material use, which requires further exploration. These findings suggest that understanding the broader systemic factors affecting CE is essential to fully realizing its potential. Moreover, the integration of AI in CE strategies emerged as a promising avenue for optimizing resource management, improving waste reduction, and enhancing productivity. AI can play a critical role in identifying inefficiencies, predicting trends, and streamlining operations in SMEs. This study contributes to the growing body of knowledge on CE in SMEs, emphasizing the importance of AI in advancing sustainability and efficiency in circular practices. Further research is needed to explore industry-specific challenges and systemic interactions in greater detail.

This paper addresses the mathematical modelling of transient processes in a steel membrane oscillating in a nonlinear viscoelastic isotropic medium. For this purpose, three types of mathematical models of the object under study with different degrees of adequacy are presented. The first type of model is presented as a system with distributed mechanical parameters, the equations of state of which are derived from the modified Hamilton‒Ostrogradsky principle and represent a mixed problem. The second is presented as a system with concentrated parameters, which is a Cauchy problem. The third type of model is presented as a modification of the second type via the fractional derivative and integral theory using the Caputo Fabrizio operator. The results of computer simulations for all types of models are presented in the form of analysed figures. Comparative analysis was also carried out for all the models on a model steel membrane with a fixed tension force, which demonstrated that the application of the Caputo–Fabrizio operator to a simplified membrane model improved the degree of adequacy of the latter.

The article presents the results of experimental studies on the symmetrical and asymmetrical rolling process of composite laminate sheets consisting of difficult-to-deform Ti and Ni materials. Composite sheets joined by explosive welding were used for the tests. The aim of the research was to determine the impact of plastic shaping conditions in the rolling process on the quality and selected functional properties of the materials constituting the layered composite. The rolling process was carried out cold on a duo laboratory rolling mill with a roll diameter of 300 mm. During the rolling process, the influence of the rolling process conditions on the distribution of metal pressure forces on the rolls was determined, as well as the shear strength and microstructural studies of the joint area of the layered composites. As part of the conducted considerations, residual stress tests were carried out using the Barkhausen noise method. The scientific aim of the presented work was to determine the optimal conditions for the plastic processing of multi-layer Ti-Ni sheets. The results presented in the work allowed for determining the most favorable conditions for the rolling process.

In this study, Artificial Neural Networks (ANN) were employed to develop a Digital Twin (DT) of the Rotary Friction Welding (RFW) process. The neural network models were trained to predict the peak temperature generated during the welding process of dissimilar Ti Grade 2/AA 5005 joints over a temperature range of 20–640 °C. This prediction was based on a parametric numerical model of the RFW process constructed using the Finite Element Method (FEM) within the ADINA System software. Numerical simulations enabled a detailed analysis of the temperature distribution within the weldment. Accurate temperature predictions are essential for assessing the mechanical properties and microstructural integrity of the welded materials. Artificial Intelligence (AI) models, trained on historical data and real-time inputs, dynamically adjust critical process parameters—such as rotational speed, axial force, and friction time—to maintain optimal weld quality. A key advantage of employing AI-augmented DT systems in the RFW process is the ability to conduct real-time (less than 0.1 s) optimization and adaptive control. By integrating a Genetic Algorithm (GA) with the DT algorithm of the RFW process, the authors developed an effective tool for analyzing parameters such as axial force and rotational speed, in order to determine the optimal welding conditions, which translates into improved joint quality, minimized defects, and maximized process efficiency.

The primary objective of the article is to justify that the ESG indicators introduced mandatorily but gradually over time in accordance with the CSRD (Corporate Sustainability Reporting Directive) to organisations, from the position of the company itself, are measures of the sustainability of their activities - core activities in convergence with environmental activities, social responsibility as well as corporate governance. In the first part of the article, the multidimensionality of ESG is indicated and the multidimensional thematic scopes of this reporting are summarised. Portfolios of quantitative and qualitative indicators in the environmental, social, corporate governance dimensions have been compiled. In turn, on the basis of the selected results of the research entitled “Evaluation of ESG reporting in the context of generating knowledge about sustainable organisations”, an attempt is made to answer two fundamental research questions that are part of the objective of the article: 1) What factors determine the sustainable activities of the surveyed organisations, to what extent are they actually relevant to the organisation and can they be assessed in the ESG dimensions? and 2) Is the development of organisations already subject to ESG reporting sustainable in all three dimensions E, S, G? The research was essentially conducted in a group of large financial companies already subject to ESG reporting, in accordance with the CSRD.

In this study, we discuss the possibility of using supramolecular clathrates as materials that exhibit quantum-dimensional properties capable of providing high-density electrical energy storage. For this purpose, nanoscale structures with supramolecular bonding based on the host-guest principle were formed. The hosts were an expanded GaSe single crystal and a nanoporous SiO2 matrix, and the guest component was an ionic liquid of two dierent chemical compositions. As a result of studies conducted by the impedance spectroscopy method, manifestations of such eects as quantum tunneling and Coulomb blockade were detected, which made it possible to accumulate an electric charge. A direct proof of this is the measured voltampere characteristics, which demonstrate a pronounced hysteresis characteristic for electrochemical current batteries. The obtained result indicates the possibility of creating fundamentally new devices for the accumulation of electrical energy with the quantum nature of the corresponding eects and phenomena. topics: supramolecular clathrates, GaSe, Santa Barbara Amorphous-15 (SBA-15), ionic liquid

The optimal technological choice for sustainable development lies in renewable energy sources (RES). However, the potential offered by RES utilization poses significant challenges for mobile technologies and everyday living. Despite extensive research and information highlighting the benefits of renewable energy, there remains considerable debate, and limited awareness persists. The advantages of RES are not fully comprehended, raising concerns about its consistent application. Regrettably, lack of knowledge and a fundamental understanding hinders effective dissemination. To gauge the attitudes of residents in regions where RES is employed, this study employed a questionnaire authored by the researcher. The study was conducted between June 2022 and January 2023, with a total of 12,428 participants completing the survey. The sampling method utilized an online form distributed via various social media channels and among local contacts of the authors in Poland, Sweden, and France. Gender allocation: 58% male and 42% female. Respondents shared their perspectives on ecology and disclosed their familiarity with RES utilization. Results indicate public skepticism regarding the adequacy of RES security measures and the level of knowledge for its effective use. Insufficient experts, limited social advocacy, and reliance on online sources contribute to a low level of awareness. In several EU countries, the absence of widely accepted and easily accessible information on renewable energy sources (RES) hinders knowledge sharing and adoption. Despite the EU’s efforts to promote renewable energy through directives and subsidies, rural communities in these countries often lack adequate education and awareness about RES technologies. This gap in knowledge contributes to unfavorable perceptions, with some residents viewing renewables as unreliable or economically unfeasible options compared to traditional energy sources like coal or natural gas. Additionally, bureaucratic hurdles and inconsistent government policies further complicate the transition to renewable energy, discouraging investment and innovation in the sector. As a result, while the EU aims for a sustainable energy future, these barriers impede the widespread growth of RES and hinder progress towards climate targets. In Poland the study found that 76% of respondents expressed favorable perceptions of RES, indicating a general inclination towards adopting clean energy solutions. In Sweden, the analysis uncovered a high level of environmental awareness among participants, with 85% of respondents expressing concern about environmental degradation. Despite this awareness, 62% of participants reported reservations about the security and affordability of energy derived from renewable sources. Additionally, 48% of respondents expressed uncertainty or ambivalence regarding the environmental benefits of RES. In France, the research revealed similar concerns among respondents regarding the security and affordability of renewable energy. 59% of participants expressed reservations about the security of energy derived from renewable sources, while 53% cited perceived high costs as a barrier to adoption. Furthermore, 41% of respondents identified underdeveloped RES infrastructure as a hindrance to wider acceptance and utilization. The quantitative data highlights the complex landscape of renewable energy perceptions and attitudes in Poland, Sweden, and France. While there is a general awareness of environmental issues and a positive inclination towards clean energy solutions, concerns about security, affordability, and infrastructure remain significant barriers to widespread adoption. These findings underscore the importance of targeted interventions and educational efforts to address these challenges and promote sustainable energy practices across Europe. Renewable energy sources (RES) represent a critical avenue for sustainable development, offering a pathway to mitigate environmental degradation and reduce dependence on fossil fuels. This study investigates public attitudes, knowledge levels, and barriers to RES adoption in rural areas of Poland, Sweden, and France, highlighting the unique socio-economic and cultural factors influencing these regions. Conducted between June 2022 and January 2023, the research utilized an online survey, gathering responses from 12,428 participants across these countries. Respondents evaluated statements on environmental responsibility, RES knowledge and application, and perceived obstacles, using a five-point Likert scale. Key findings reveal that while environmental awareness is high, significant barriers persist in the form of limited knowledge, underdeveloped infrastructure, and perceptions of high costs associated with RES. In Poland, 76% of respondents expressed a positive view of RES but cited concerns about cost and security. Swedish participants demonstrated strong environmental awareness (85%), yet 62% voiced reservations about RES affordability and reliability. French respondents similarly highlighted concerns regarding infrastructure and costs, with 41% identifying underdeveloped RES systems as a primary hindrance. The study underscores the importance of targeted educational campaigns and policy interventions to bridge knowledge gaps and foster greater acceptance of RES. Tailored strategies addressing local barriers—such as financial incentives, community-based advocacy, and infrastructure investments—are essential to overcoming these challenges. By exploring diverse perspectives and barriers across the three countries, this research contributes valuable insights to the broader discourse on sustainable energy transitions in the EU.

Computational intelligence (CI) and machine learning (ML) have evolved into foundational pillars of modern data-driven research, with growing impacts across domains such as engineering, medicine, finance, and environmental science [...]

In this study, the cumulative effect of the empirical probability distribution of a random variable is identified as a factor that amplifies the occurrence of extreme events in datasets. To quantify this observation, a corresponding information measure is introduced, drawing upon Shannon entropy for joint probabilities. The proposed approach is validated using selected market data as case studies, encompassing various instances of extreme events. In particular, the results indicate that the introduced cumulative measure exhibits distinctive signatures of such events, even when the data are relatively noisy. These findings highlight the potential of the discussed concept for developing a new class of related indicators or classifiers.

Artykuł analizuje etykę zawodową coacha, podkreślając unikalne zasady, takie jak poufność, odpowiedzialność za rozwój klienta i unikanie konfliktu interesów. Coachowie są zobowiązani do utrzymywania relacji opartej na szacunku, bez manipulacji. Przedstawiono normy samodoskonalenia, oceny kompetencji oraz kluczowe kodeksy etyki organizacji ICF i EMCC, które stanowią fundamenty dla praktyków. Artykuł prezentuje również praktyczne podejście do stosowania standardów etycznych w pracy coacha.

Współczesne przedsiębiorstwa coraz częściej kładą nacisk na zarządzanie różnorodnością jako kluczowy element strategii rozwoju. W kontekście globalnych trendów demograficznych oraz zróżnicowanych potrzeb konsumentów staje się to niezbędnym narzędziem dla przedsiębiorstw dążących do utrzymania konkurencyjności. Korzyści wynikające z wdrażania zarządzania różnorodnością obejmują między innymi umocnienie kultury organizacyjnej, poprawę reputacji firmy, wspomaganie rekrutacji i retencji talentów, zwiększenie motywacji i efektywności pracowników oraz stymulowanie innowacyjności i kreatywności w zespole. Wdrażanie zarządzania różnorodnością wymaga dostosowania strategii do zmieniających się oczekiwań i wartości pracowników. Celem pracy jest dokonanie analizy postrzegania wybranych aspektów różnorodności występujących w miejscu pracy z perspektywy pracowników różnych grup wiekowych. Badanie skupia się na identyfikacji kluczowych różnic i podobieństw w percepcji tego zagadnienia.

Problems of computing a slewing bearings static carrying capacity have been presented in the paper. Particularly it was concentrated on determination of static limited load curves which include axial forces, radial forces and tilting moments. A calculation were performed on the base of single-row ball slewing bearing with four-point contact zone. In this work a procedure of determining the static limiting load curves on the basis of modeling by using the finite element method (FEM), analytic Eschmann’s formulas and classical mechanics equations have been described. The structure of FEM bearings’ model was considered with gear conditions between a toothed bearing’s ring (rim) and a drive pinion in a power train of the excavator F250H symbol. Moreover, in the model flexibility of: the bearing rings, a contact zone ball-bearing, support structure and mutual interactions between bolts clamping the bearing rings and the support structures were taken into account. The static carrying capacity of the analyzed bearing, considered with the pinion and without was compared. Quantitative assessment of loads of the contact zones ball-raceway was achieved by using a statistic criterion.

The consistently growing demand for robust automated Photonic Integrated Circuits assembly, testing and packaging, is increasingly oriented towards high volume and continuously sets newer challenges to overcome concerning throughput and cost effectiveness. Production processes’ intrinsic complexity, combined with short product life cycle and the necessity of quickly ramping up those to high volume, requires smarter solutions to guarantee high yield as well as low cycle time. Robust production demands for motion systems capable to realize repeated movements with precision and resolution in the range of tens of nanometers. These constraints on precision do not allow to operate the system at its highest overall speed; ideal working conditions are thereby preserved by slowing down motion, ending up trading cycle time for precision. Finally, the optimal trade-off between motion speed and repeatability is also expected to depend on hardware conditions and its optimization is therefore impossible without scheduling downtime and performing long evaluation processes. In this paper it is presented a solution for predicting linear stages’ motion inaccuracies from controller features by means of Machine Learning and Deep Learning modeling. The proposed formulation introduces a metric for calculating motion analytical imprecision that includes only the difference between successive position measurements, thus allowing a separation of short term repeatability from other error terms by removing the mean from the evaluation. Successive differences are interpreted as single-motions’ expected errors that can be aggregated into a repeatability estimate, serving as target distribution for the learning problem; predictions of single-motion metrics ensure the proposed approach to work in production scenarios when non identical movements are performed, opening up the possibility to realize advanced control paradigms and predictive maintenance for smart manufacturing.

In this paper, a novel multiple-input operational transconductance amplifier (MI-OTA) is proposed. The MI-OTA can be obtained by using the multiple-input bulk-driven MOS transistor (MIBD MOST) technique. The circuit structure is simple, can operate with a supply voltage of 0.5 V, and consumes 937 pW at a current setting of 625 pA. The proposed MI-OTA was used to implement a high-order multiple-input voltage-mode universal filter. The proposed filter can provide non-inverting and inverting low-pass, high-pass, band-pass, band-stop, and all-pass transfer functions to the same topology. In addition, it has a high input impedance and does not need any inverted input signals, so there is no additional buffering circuit. The proposed filter can be used for biological signal processing. The proposed MI-OTA and the second-order universal filter were simulated in Cadence using CMOS process parameters of 0.18 μm from TSMC to verify the functionality and performance of the new structures.

In the present paper, the theoretical simulation and experimental studies of magnetic properties of the Mn0.9Zn0.1CoGe alloy was done. Field dependences of magnetization in a wide range of temperatures were collected. Based on the thermomagnetic Maxwell relation, the magnetic entropy change ∆SM was calculated. Moreover, using the phenomenological model, temperature dependences of magnetization in a wide range of elds were simulated. Values of thermomagnetic properties, such as magnetic entropy change and refrigeration capacity, were calculated. topics: MM'X alloy, magnetocaloric eect (MCE), X-ray diraction (XRD), magnetocaloric properties

The aim of the present paper was to study the chaotic behavior in a resistor-inductor-diode circuit induced by modulation of voltage amplitude. Time evolutions of the voltage or current signal revealed an extremely chaotic response of the simulated system. These dependences were taken into account in the construction of the phase space. Moreover, based on a bifurcation diagram, the Feigenbaum constant was calculated and verifed with reliable and noticeable accuracy.

This paper presents a multiple-input single-output (MISO) shadow filter implemented using multiple-input differential difference transconductance amplifiers (MI-DDTAs). The MI-DDTA’s multiple inputs are realized through the multiple-input bulk-driven MOS transistor (MI-BD MOST) technique. Leveraging the multiple-input capability of the DDTA, various filter responses—low-pass filter (LPF), high-pass filter (HPF), band-pass filter (BPF), band-stop filter (BSF), and all-pass filter (APF)—can be efficiently achieved by appropriately configuring the input signals. The natural frequency and quality factor of the shadow filter can be independently tuned using external amplifiers. Unlike conventional shadow filters, where adjusting the quality factor or natural frequency impacts the passband gain, this design ensures a constant unity passband gain. The MI-DDTA operates at a supply voltage of 0.5 V and consumes 385.8 nW of power for setting current Iset = 14 nA. The proposed MI-DDTA and shadow filter are designed and validated through simulations in the Cadence design environment, using a 0.18 µm CMOS process provided by TSMC (Taiwan Semiconductor Manufacturing Company Limited).