Industry 4.0
Vol. 10 (2025), Issue 2

Table of Contents

  • TECHNOLOGICAL BASIS OF “INDUSTRY 4.0”

    • Location estimation using Wi-Fi media access control address and device miniaturization

      pg(s) 43-46

      When location was estimated using Sigfox’s Atlas Wi-Fi, the estimation error is several hundred meters. Meanwhile, when location was estimated using the Wi-Fi media access control (MAC) address and HERE’s API, the estimation error was ~10 m. In an Internet of Things device that obtains the Wi-Fi MAC address, the combination of exp32 and 100a was ~1/5th of the combination of Arduino R4 and Sigfox Shield.

    • MESWARM: A Modular and AI-Driven Manufacturing Execution System for Industry 4.0

      pg(s) 47-52

      The rapid advancement of Industry 4.0 technologies has significantly transformed manufacturing environments, necessitating the adoption of intelligent and scalable solutions. MESWARM is a modern platform designed to digitize and optimize manufacturing processes, offering industrial enterprises a means to enhance efficiency, reliability, and sustainability. By integrating traditional Manufacturing Execution System functionalities with cutting-edge technologies such as Artificial Intelligence and the Internet of Things, MESWARM provides a flexible, modular system tailored to specific production needs. It’s architecture and key functionalities are outlined, highlighting its core modules such as Configuration, Production Management, and IoT. The potential of future modules, including Service Management, Adaptive Logic, Energy Management, Document Management, and AI-driven analytics, is also explored. By leveraging real-time data collection and analysis through MQTT-based communication, MESWARM facilitates precise production monitoring and predictive maintenance, minimizing downtime and enhancing operational decision-making. Real-world implementations are examined, showcasing its impact on production efficiency and system scalability.

  • DOMINANT TECHNOLOGIES IN “INDUSTRY 4.0”

    • 2D graphene layers in chemiresistive sensors

      pg(s) 53-55

      In this paper, a two-dimensional (2D) material graphene with exceptional electronic and mechanical properties is discussed as a promising candidate for chemiresistive sensor applications. High surface area and superior charge carrier mobility of graphene enable rapid and sensitive detection of gaseous analytes, making it an attractive alternative to conventional metal oxide semiconductor (MOS) sensors. The review of recent advancements in graphene-based chemiresistive gas sensors is done, highlighting their operational principles, fabrication techniques, and performance enhancements through material modifications such as reduced graphene oxide (rGO). Additionally, we examine the application of graphene sensors in environmental monitoring, where their ability to detect pollutants like NO₂ , NH₃ , and CO₂ with high sensitivity and low power consumption provides a significant advantage over traditional sensing technologies. Despite these advancements, challenges such as selectivity, standardization, and sensor stability remain critical areas for future research.

    • Ionospheric Radio Reflection Analysis System Solar Flare and Sunrise/Sunset Interference Detection

      pg(s) 56-59

      Traditionally, solar flare detection has been achieved through methods that rely on the presence of expensive satellites. We propose an alternative method that produces reliable detection of solar flares in a cheap and conveniently earth-based way. This paper discusses the design, practical implementation, demonstration of functionality and usefulness of a reception and monitoring system for VLF (Very Low Frequency, 3 kHz–30 kHz) radio signals, transmitted by stations located thousands of kilometers from the reception point, that can be used to accurately detect solar flares. We chose this frequency range because VLF radio waves are efficiently reflected by the lower layers of the ionosphere, and diurnal or sudden changes in these layers cause corresponding variations in the received signal level over long distances (over 1000 km).

    • Isentropic analysis of the complex three cylinder steam turbine from municipal solid waste power plant

      pg(s) 60-63

      In this paper are presented isentropic analysis results of a steam turbine and each of its cylinders which operate in Municipal Solid Waste (MSW) power plant. Low Pressure Cylinder (LPC) which produces the highest real mechanical power has the lowest isentropic loss of all cylinders equal to 4344.75 kW, while High Pressure Cylinder (HPC) which produces the lowest real mechanical power has the highest isentropic loss of all cylinders equal to 5204.54 kW. Isentropic losses and isentropic efficiencies are reverse proportional, because the cylinder with the lowest isentropic loss (LPC) has the highest isentropic efficiency equal to 88.92%, while the cylinder with the highest isentropic loss (HPC) has the lowest isentropic efficiency equal to 84.58%. Surprisingly, isentropic efficiency of the Intermediate Pressure Cylinder (IPC) is equal to 86.80% only, which is higher in comparison to HPC but notably lower than LPC. The observed turbine strongly differs from other comparable steam turbines from the literature where IPC has notably higher isentropic efficiencies than both HPC and LPC. Whole observed steam turbine produces real mechanical power equal to 97513 kW, while its isentropic efficiency is equal to 86.87%.

    • Mechanical characterisation of Babbitt Alloys solidified under different conditions

      pg(s) 64-67

      This paper investigates the mechanical behaviour of SnSb11Cu6 Babbitt alloys solidified under pressure and under atmospheric conditions. Quasi-static tests were performed at three different constant strain rates: 0.001 s⁻ ¹, 0.003 s⁻ ¹, and 0.01 s⁻ ¹, while dynamic tests were conducted at strain rates corresponding to impact speeds of 10 m/s and 20 m/s. The results indicate that alloys solidified under atmospheric conditions exhibit higher compressive strength in the quasi-static regime than those solidified under pressure. However, as the impact speed increases to 1400 s-1 the compressive strength of both materials converges. Beyond this rate (up to 2800 s⁻ ¹), the alloy solidified under pressure shows a slight performance shift, suggesting better property stability at higher loading rates. Overall, the alloy solidified under atmospheric conditions offers superior performance for low-strain applications, whereas the alloy solidified under pressure demonstrates more stable properties under high-strain loadings. These findings offer valuable insights for the selection and design of materials in tribological systems, particularly where performance varies under different loading conditions.

  • BUSINESS & “INDUSTRY 4.0”

    • Augmented Analytics platform and Service 4.0 solution for service excellence

      pg(s) 68-70

      In the modern era, it is a challenge to develop a high-quality business product that adequately serves its real purpose, by implementing Machine Learning (ML) and Large Language Models (LLM), both generally defined as AI. For this reason, Danlex 78 proposes a multilayer approach for developing an augmented analytics platform and Service 4.0 solution to accomplish service excellence in x-ray inspection systems. In this approach, AI is important, but still just a tool for achieving targeted business goals. The complex ecosystem of business knowledge combined with science and technology leads to our working solution. This article presents our approach and marks the most important KPIs for achieving service excellence in X-ray inspection systems maintenance.

    • Digital Transformation in Human Capital Management in Tourism

      pg(s) 71-74

      This report identifies the drivers and challenges of tourism human capital management under the conditions of ubiquitous digital transformation. Major attention was paid to integration of opportunities of the existing technologies caused by the penetration of artificial intelligence in all spheres of the tourism industry, while preserving the which will give way to harmonious interaction and will create technological intelligence.

    • The impact of AI on entrepreneurship education

      pg(s) 75-78

      The AI’s role in life has increased significantly since the initial introduction of ChatGPT. This trend has drawn the attention of scholars to numerous topics and the entrepreneurship education is one of them. There is already research on the potential of AI in entrepreneurship education and the current paper aims at identifying benefits of AI for entrepreneurship education alongside with potential risks and challenges of its application. The results show that AI can contribute to more personalized education with real environment simulations. Alongside it can improve the assessment. However, challenges like date security, overdependence on AI and AI biases, need to be addressed. The findings identify the need for future examination of specific cases and may contribute to the development of regulations, ethical consideration and development of practices in implementing AI in entrepreneurship education.

  • SOCIETY & ”INDUSTRY 4.0”

    • A comparison of Computer Forensic Tools

      pg(s) 79-81

      This paper discusses key challenges and methods in computer forensics and presents a comparative analysis of forensic software tools FTK, Autopsy, The Sleuth Kit TSK, TestDisk and Foremost. The instruments considered in the study are applied in different case studies to collect, analyze and preserve digital evidence available for computer forensics, cybersecurity and cloud-based investigations. The research discusses their effectiveness and limitations in handling cloud-based evidence collection.

    • A mobile application for Android supporting self-study in technical sciences

      pg(s) 82-84

      Nowadays advancing world of technology, mobile applications are rapidly growing segment of global mobile market. The proposed application aims to support self-learning of students, but also to facilitate the learning process, by offering a teaching panel where courses can be created and lectures can be added to them. The application was designed using the Android Studio programming environment and was written in the Java programming language. It is fully dynamic, as all information entered by the user being stored in a database.

    • A Review of the Modern Software Systems and Tools in Logistics for Digital and Smart Manufacturing

      pg(s) 85-92

      Logistics represents an industrial and multidisciplinary scientific field that deals with the analysis, planning, management, and control of all logistics operations (distribution, warehouse, shipping, transportation etc.). Modern trends in logistics involve the use of advanced software systems, tools and digital technologies (DT) to address all operations and activities within a single logistics task. Digital technologies (DT) in logistics encompass the application of intelligent and smart digital technologies, smart technologies (ST), smart manufacturing (SM), smart logistics (SL), artificial intelligence (AI), cloud computing (CC), data mining (DM), and more. The application of all these technologies in logistics has created a new concept called Logistics 4.0, which is based on the concept of Industry 4.0. While SMEs (small and medium-sized enterprises) and corporations in middle-developed and underdeveloped countries of the world are beginning to think about introducing the concept of Logistics 4.9, a new concept of Logistics 5.0 has already been created and defined. Within the Logistics 4.0 concept, which is part of Industry 4.0, advanced and modern versions of software systems and tools in the field of logistics are used for planning, transportation, warehousing, distribution and other logistics operations. Modern software systems and tools for logistics are classified into several groups: logistics database (LDB) for quick search and access of logistics data, logistics information systems (LIS) for storing, processing and management of logistics data and information, logistics management systems (LMS) for managing logical operations, logistics decision support systems (LDSS) for decision-making in specific logistics operations, logistics expert systems (LES) and other software systems and tools for logistics operations. This paper provides an overview of different software systems and tools for logistics operations.