The article aims to mathematically model processes that occur in non-metallic heterogeneous materials when active thermography methods were used for deep study control. Currently, the trend in industrial development is using non-metallic heterogeneous mediums as a system of various components as structural materials. Such materials are characterized by improved physical and mechanical properties, which can be adjusted by selecting compositions and the ratio of component phases and macrostructure. At the same time, they are characterized by disadvantages such as variability of volume and time properties and the presence of various defects. Effective control methods are of particular importance to ensure the quality and reliability of products made from materials of this class. In the article, the authors analyzed the capabilities of existing non-destructive testing methods for flaw detection of products made of non-metallic heterogeneous materials. When developing a new and improving an existing measurement method, the problem of establishing a set of radiation parameters was used. This allowed for describing the state of the material with the necessary accuracy and the functional connections of these parameters with the latter’s characteristics.

: It is known that in recent years there have been major changes in all branches of industry, especially in the automotive and electro-electronic industry, because new business methods are on the scene, and production processes are being transformed so that they are flexible. In the automotive and electro-electronic industry, the leading technology is robotic technology, the application of which increases the return on investment. Advanced robotics as the basic technology of Industry 4.0 in the new era of production in the automotive and electro-electronic industry plays a very important role because it enables: mobility, readiness, reliability, adaptability, transformation of production, integration with machines, increase of flexibility, improvement of quality, storage and production systems integrated as Cyber-Physical Systems, workers are freed from routine and repetitive tasks. The paper provides an overview of applied and issued patents in robotic technology, the application of robots in the World and China as the leader in the implementation of robotic technology in the world. An analysis of the implementation of industrial robots, as well as advanced robots in the automotive and electro-electronic industries of China, is given, as well as the forecast of the application in the coming years.

Using AI through industries and business processes is increasingly becoming the subject of theorists and practitioners. In the HRM process, the use of AI gives companies numerous advantages in employee performance, and processes, but also presents them with organizational, financial, technical, legal, and personnel challenges. This paper explores the application of AI systems in recruitment and selection through gamification strategies, people analytics, talent intelligence, AI platforms, video interviews, and conversational AI. It provides an overview of the benefits and challenges associated with their implementation. Additionally, the paper delves into ethical considerations and legislation, focusing on the EU Act, domestic laws, and ISO AI standards. The primary goal of this paper is to provide a comprehensive understanding of AI's role in HR processes and the complexities of implementing AI solutions in recruitment and selection.

In the last ten years, the development and research of advanced technologies, as well as their application in all segments of society, have led to major changes and reshaping of the new world. New innovations are occurring on a daily basis, but their application is not going fast enough due to the rigid infrastructure. However, in order to secure an optimal future, we all have to adapt to the changes that are coming. The developed countries have adopted the strict implementation of advanced technologies of Industry 4.0, some of which include: Internet of Things (IoT), Big Data, Cloud Computing, smart sensors, Radio Frequency Identification (RFID), 3D printing, advanced security systems, Virtual and Augmented Reality (VAR), etc. Robotics is the basic and first technology that has been implemented since the 60s of the last century, with artificial intelligence coming in the spotlight in the last ten years. Artificial intelligence is becoming a key to the development of advanced robots, as it enables them to adapt to unpredictable situations, to learn from experience and make intelligent decisions.Robots use AI to process sensor data, navigate, recognize objects, plan paths and interact with the environment. In short, artificial intelligence enables robots to be smart, whereas robotics uses AI to create autonomous and useful devices. This symbiosis contributes to progress in many industries, including healthcare, manufacturing and transportation. Artificial intelligence (AI) and robotics are two key fields that complement each other. The paper presents the trend of applied and approved patents in artificial intelligence and robotics, as well as an example of the use of artificial intelligence in advanced robots to perform certain tasks. Artificial intelligence (AI) is having an increasing impact on robotics, opening up many possibilities.

In recent advancements in robotics, Artificial Intelligence (AI) methods such as Deep Learning, Deep Reinforcement Learning (DRL), Transformers, and Large Language Models (LLMs) have significantly enhanced robotic capabilities. Key AI models driving advancements in robotic vision include Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), the DEtection Transformers (DETR), the YOLO family of algorithms, segmentation techniques, and 3D vision technologies. Deep Reinforcement Learning (DRL), an AI technique where agents learn optimal behaviors through trial and error interactions with their environment, enables robots to perform complex tasks autonomously. Transformers, originally developed for natural language processing, have been adapted to robotics for tasks involving sequence prediction and data understanding, improving perception and decision-making processes. LLMs leverage vast amounts of text data to enhance robot-human interaction, enabling robots to understand and generate human-like language, thus improving their communicative and collaborative abilities in various applications. The integration of these AI methods enhances the adaptability, efficiency, and overall performance of robotic systems, paving the way for more sophisticated and intelligent autonomous agents.

The first industrial robots appeared in the production processes of the 60s of the last century, and they are implemented to this day in all production processes in the world. The biggest application of industrial robots has been found in three industries in the world: the automotive industry, the electrical/electronic industry and the metal industry. The automotive industry is the first to implement the most industrial robots, and in recent years the electrical/electronics industry has also joined in, as these two industries in the world implement more than 60% of the total industrial robots implemented in the world. The use of industrial robots has been used to perform those tasks that are tiring and hazardous to the health of workers, which include welding, and the performance of these operations is mostly n the automotive industry. To date, the most implemented industrial robots of the first generation, which are robustly surrounded by fences (for the protection of workers), take up a lot of space and are complicated to reprogram. Development of new technologies such as: sensor technology, Internet of Things (IoT), big data, „cloud computing“, virtual and augmented reality (AR), artificial intelligence (AI), advanced security systems and others is credited with the development of robotic technology. In this paper is shown the trend of implementing industrial robots and their role in the welding process.

Since the introduction of the concept of Industry 4.0 until today, the world is facing a series of changes resulting from intensive scientific, technical and technological innovations. Research, innovation and development changes are aimed at improving production, business and everyday life through the application of basic technologies of Industry 4.0. In order for individuals, organizations, communities and states to be able to use the benefits of these improvements, it is necessary to rapidly adapt to all innovative trends: developing the necessary skills of individuals and groups for the adoption and use of these technologies, the implementation of technologies in companies, organizations and institutions, and the development of appropriate strategies that these processes would be managed and directed. In the developed world, these I 4.0 implementation processes are already reaching their maturity: educational programs are adapted to the needs of monitoring technical-technological changes, companies deal with solving challenges related to these processes after the implementation of Industry 4.0 technologies, and states and communities are working on devising further directions of development and a strategy that will further accelerate changes. In Bosnia and Herzegovina, the processes are somewhat slower: educational programs partially follow the needs of education for Industry 4.0, companies struggle with the challenges of adopting and implementing Industry 4.0 without adequate institutional support, and strategies related to exploiting the opportunities of Industry 4.0 have not been developed, both due to the lack of initiative, as well as due to administrative restrictions related to the complex political system of Bosnia and Herzegovina. Considering that, this paper presents the results of research on the representation of Industry 4.0 technologies in the economy and education of Sarajevo Canton. The sample on which the research was conducted included 105 companies and 239 respondents from the general population. The results show that the highest level of application of Industry 4.0 technologies exists in the part related to the advanced management of company resources using planning and management support systems, and in communications. These findings, as well as the results related to the established level of knowledge of Industry 4.0 technologies in the general population, speak in favor of the need for the urgent development of various educational programs that will accelerate the learning of Industry 4.0 among all members of the community, as well as the establishment of state programs to support the implementation of technologies in companies, so that the economy of the Canton and the country as a whole would not fall behind in relation to the world driven by the fourth industrial revolution.

The implementation of disruptive technologies of Industry 4.0 is carried out in all segments of society, but we still do not fully understand the breadth and speed of its application. We are currently witnessing major changes in all industries, so that new business methods are emerging, as well as transformation of production systems, new form of consumption, delivery and transport. All this is happening due to the implementation of disruptive technological discoveries that include: the Internet of Things (IoT), advanced robotics, smart sensors, Big Data, analytics, cloud computing, 3D printing, machine learning, virtual and augmented reality (AR), artificial intelligence, and productive maintenance. Advanced robotics is one of the most important technologies in Industry 4.0. The robotic application in the automation of production processes, with the support of information technology, leads us to ‘’smart automation’’, i.e., ‘’smart factory’’. The changes are so profound that, from the perspective of human history, there has never been a time of greater promise or potential danger. New generation robots have many advantages compared to the firstgeneration industrial robots such as: they work alongside with workers, workers perform their tasks in a safe environment, robots take up less space, robots do not need to be separated by fences, robots are easy to manipulate and cheaper to implement. The paper analyzes the trend of implementation of collaborative and service robots for logistics, which make the automation of production processes more flexible. Robotic technology is the basic technology of Industry 4.0, because without its application, the implementation of Industry 4.0 would not be possible. The trend of application of new generation robots will have an increasing character in the future, because the goals of the fourth industrial revolution cannot be achieved without collaborative robots. In other words, the objective is to achieve a ‘’smart production process’’ or ‘’smart factory’’.

Digital twins represent a new paradigm that brings fundamental changes to business and asset management. The proliferation of connected devices and sensors has generated vast amounts of data from physical assets and processes. Digital twins leverage this data to create a virtual counterpart that reflects the behavior, performance, and characteristics of their physical counterparts in real-time. The definition of digital twins encompasses a wide range of applications and contexts. This paper provides an overview of existing literature on digital twins, including their definition, key characteristics, and classification. Additionally, it highlights potential challenges and limitations associated with digital twins and identifies the technologies that enable their implementation. By understanding the fundamental concepts and technological advancements in the field of digital twins, organizations can harness their potential to enhance their business, optimize resources, and foster innovation. Numerous examples of digital twin applications in various industries are highlighted in this paper, with a particular focus on the elevator industry. Therefore, this paper serves as a comprehensive source of information for researchers, practitioners, and decision-makers who wish to explore the application of digital twins in different industries and domains.