International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

Digital twin technology has rapidly evolved into a foundational pillar of modern engineering practice. By creating high-fidelity, data-driven virtual replicas of physical systems, digital twins enable continuous monitoring, predictive analytics, and advanced optimization throughout the lifecycle of assets. This extended article expands on the conceptual, technical, and practical dimensions of digital twins, providing deeper insights into architectures, data frameworks, integration strategies, real-world case studies, economic implications, and emerging research directions.

This study investigates the electrochemical performance of Sacrificial Anode Cathodic Protection (SACP) systems for offshore steel structures using Finite Element Analysis (FEA). Two structural substrates, S235JR carbon steel and S550QL high-strength steel, were modelled in a 3 wt.% NaCl electrolyte. A comparative analysis was performed between two sacrificial anode materials: a conventional Al- 5Mg alloy and a quaternary Al-6Zn-0.2In-1Mg-0.03Ti alloy. The simulations evaluate the influence of anode placement errors by comparing an ideal symmetric distribution (90°) with a clustered configuration (10°). The results show that geometric clustering significantly alters the potential distribution along the structure. For S235JR steel, the clustered configuration produces localized underprotection with potentials reaching −0.78 V (vs. Ag/AgCl). In contrast, for S550QL steel, the same configuration results in localized over-polarization (≈ −0.96 V), thereby increasing the risk of hydrogen-induced stress cracking (HISC). The study demonstrates that improper anode placement may compromise cathodic protection efficiency even when high-performance anode alloys are used. These findings highlight the importance of accurate anode distribution and support the use of numerical simulations in digital twin approaches for offshore corrosion management.

The article The article describes a simulation experiment to assess human behavior during threats inside buildings, using Metaverse systems and virtual reality (VR). The study was carried out on a model of a real building, where avatars controlled by users simulated responses to crises. This approach has several advantages over the traditional use of NPCs (non-player characters). Usercontrolled avatars enable a more realistic representation of behavior, as participants can make decisions in real time depending on the developing situation. Unlike NPCs, whose reactions are pre-programmed and predictable, human-controlled interactions introduce an element of unpredictability and authenticity, better reflecting real human reactions. Thanks to Metaverse and VR systems, it is possible to precisely reproduce building interiors and threat scenarios, which allows for analyzing various evacuation strategies and behaviors in stressful situations. In addition, experiment participants can repeatedly participate in various simulations, which increases the scope of collected data and allows for a more comprehensive analysis. The article emphasizes that using Metaverse and VR systems for simulations with users brings significant benefits to research on security and crisis management. This approach allows for the creation of more realistic models of human behavior, which are key to improving evacuation procedures and responses to threats inside buildings. The study presents the results of research carried out based on an original solution implemented in the Metaverse environment.

The idea of creating and using digital twins has been strongly influenced by the process of integrating artificial intelligence methods with big data analytics of data from Internet of Things (IoT) devices. The concept of “Digital Twin” has become increasingly influential and culminating in the field of CPS. The main objective of the study is to define the basic requirements to the digital twins for cyber-physical system and based on the different definitions and components of digital twins, to summarize and analyze approaches, methods and tools used for their development. This analysis should serve as a basis for the development of a methodology for creating digital twins for cyber-physical manufacturing systems in the process industry.

The digital twin (DT) based on CMM as support Industry 4.0, are based on integration of digital product metrology information through metrological identification, application artificial intelligence techniques and generation of global/local inspection plan for coordinate measuring machine (CMM). DT based on CMM has an extremely expressed requirement for digitalization, control, and monitoring of the measurement processes inside Industry 4.0 concept. This paper presents an approach of development DT as one direction information flow based on four levels: (i) mathematical model of the measuring sensor path; (ii) tolerances and geometry of the parts by applying an ontological knowledge base; (iii) the application of AI techniques such as Ants Colony Optimization (ACO) and Genetic lgorithm (GA) to optimize the measurement path, part number of part setup and configuration of the measuring probes; (iv) simulation of measurement path. After simulation of the measurement path and visual checks of collisions, the path sequences are generated in the control data list for appropriate CMM. The experiment was successfully carried out on the example of prismatic part.

This year we have open a new laboratory of automation and robotics in the Department of Technical Studies at the College of Polytechnics in Jihlava. Our laboratory is equipped with a FESTO CP Factory production line in the biggest configuration in the middle Europe. This system which includes physical components and many virtual tools can be used in education, research and cooperation with industrial companies.

Technology and innovations have powered the evolution of Industry4.0, the fourth industrial revolution.
State-of-the-art technologies such as the Internet of Things (IoT), cloud computing (CC), big data analytics (BDA), and artificial intelligence (AI) – all part of Industry4.0, have greatly stimulated the building industry. Digital Тwin is a significant enabler for Industry 4.0 initiatives. Within Industry 4.0, the amount of digital product information generated and collected over the entire lifecycle has been growing.
Although digital twins have been around for several decades, the rapid rise of the internet of things (IoT) is that they have become more widely considered as a tool of the future. Digital twins are getting attention because they also integrate things like artificial intelligence (AI) and machine learning (ML) to bring data, algorithms, and context together
A ―digital twin‖—or digital replica of a physical entity—can target building industry in several sub-areas:
– Facility management
– Product Lifecycle Management
– Smart Buildings
– Smart energy
All these areas are one giant step further by creating a Digital Twin — a virtual representation of real-world buildings that can be viewed and scrutinized in minute detail. This research describes business cases and best practices in design of IoT Solutions for building industry, powered by Digital Twins. A reference architecture and prototypes which demonstrate application of Digital Twins in Smart are created as a result of this study .This research is technology agnostic, but prototypes of sample solutions are considered in the context of Microsoft Azure (Azure solutions, covering Azure Digital Twins Service and Azure IoT Stack.)