CEPT AND KEY TECHNOLOGIES OF INDUSTRY 4.0 IN THE ENERGY SECTOR

Анотація

The purpose of this work is to highlight that the integration of cloud computing, artificial intelligence, IoT, and big data analytics under Industry 4.0 is key to revolutionizing the energy sector. This convergence of technologies not only enhances efficiency and drives innovation but also supports the sustainable transformation of energy production. Also, the future success of the energy industry hinges on its capacity to adapt to these advancements, thereby creating a seamless, digitally empowered, and environmentally responsible industrial ecosystem.

Industry 4.0 is widely recognized as the conceptual framework for the fourth industrial revolution, representing a paradigm shift in manufacturing and production systems. At its core, Industry 4.0 involves the integration of intelligent machinery and advanced digital technologies to enhance the efficiency of the supply chain and enable comprehensive monitoring and analysis of production processes. This concept encompasses a range of methods, including big data analytics, artificial intelligence, the Internet of Things (IoT), and cloud computing, all aimed at optimizing production efficiency and overall supply chain performance.

Historically, humanity has experienced three distinct industrial revolutions since the 19th century, each ushering in significant productivity gains and transforming work practices. The advent of Industry 4.0, as the fourth revolution, marks a transition toward intelligence, interconnectivity, and digitalization within the manufacturing sector. This revolution carries the critical mandate of steering the evolution of global industrial practices, fundamentally altering the operational landscape of production systems [5,6].

From a conceptual standpoint, the application of Industry 4.0 in the energy sector involves the digital modernization of traditional energy production systems. By leveraging digital technologies, the sector can overcome inefficiencies inherent in conventional production methods such as delays and errors caused by disparate processes, which often lead to reduced efficiency and resource wastage. The integration of Industry 4.0 technologies into traditional energy workflows facilitates the sharing of information across a unified platform, enabling real-time data exchange and inter-departmental collaboration. This enhanced connectivity allows for precise, data-driven energy production, which in turn improves overall operational efficiency.

A critical examination of Industry 4.0 reveals that its primary technological pillars, namely IoT, [1] big data analytics, artificial intelligence, and cloud computing are instrumental in driving these efficiencies. The IoT, for example, plays a pivotal role by connecting devices and machinery to the internet, thereby enabling continuous data collection and sharing. Each connected device is uniquely identified and capable of communication via common devices such as smartphones. This seamless information exchange is fundamental to the development of a fully integrated production network.

Moreover, Industry 4.0 enables machine-to-machine (M2M) communication, which significantly accelerates decision-making processes and decentralizes analytical tasks. Cyber-physical systems (CPS) serve as the interface between the physical and digital realms, facilitating autonomous operations in robotics, drones, cybersecurity measures, additive manufacturing, and augmented reality applications. The evolution from Industry 3.0 to Industry 4.0 is characterized by a marked increase in production efficiency, largely attributed to these sophisticated M2M interactions enabled by both wireless and wired communication networks. The design of such systems necessitates a robust and secure framework to ensure worker safety and operational reliability.

The transformative potential of Industry 4.0 lies in its capacity to integrate advanced digital technologies into industrial processes, thereby revolutionizing traditional production systems and enhancing the efficiency of global supply chains. The implications for both manufacturing and energy sectors are profound, offering new opportunities for innovation and significant improvements in productivity. Future research and development in this area should focus on refining these digital methodologies and ensuring their seamless integration into diverse industrial contexts [2].

In the process of energy extraction, especially in the energy transmission link, many errors occur in traditional production technology, affecting the final extraction data and overall efficiency. The intervention of the Internet of Things (IoT) can mitigate these issues by enabling real-time monitoring of transportation equipment, identifying safety hazards, enhancing equipment reliability, reducing failure rates, and lowering maintenance costs.

Due to Industry 4.0 trends such as digitalization and online process monitoring, the volume of generated data is constantly increasing, this is commonly referred to as “big data”. Big data is not only pivotal in the industrial sector but also has broader applications in various business areas. It encompasses challenges related to the exponential growth, diversity, and rapid generation of data, which in turn can lead to processing difficulties. Consequently, organizations that systematically leverage big data in decision-making and strategic planning will gain a competitive edge. Big data analysis technologies offer enterprises valuable insights by enabling precise planning, reducing operating costs, forecasting potential value extraction, and optimizing production processes. Furthermore, such analytical techniques can be applied to price forecasting and risk management in the energy market, assisting both enterprises and the energy industry in making informed decisions in a complex and dynamic environment [3].

The application of artificial intelligence (AI) in the energy technology industry is continuously expanding. During energy production, AI can control and adjust machine parameters using robust algorithms to achieve optimal process control, thus improving efficiency and reducing pollutant emissions. Moreover, AI can perform hazardous tasks in energy mining, which not only boosts production efficiency but also protects human operators from dangerous conditions. By accurately assessing equipment conditions and predicting failure rates, AI facilitates timely maintenance and prolongs the service life of machinery, thereby reducing overall costs. For example, Amazon’s success illustrates how AI-driven machine learning can manage real-time logistics without human intervention, enhancing productivity, saving time, and improving service quality. In many cases, AI even surpasses human capabilities in tasks requiring mechanical precision and analytical rigor. The integration of Industry 4.0 technologies with AI promises substantial benefits for the energy sector, paving the way for a transformative digital revolution in production processes.

Building on these advancements, the synergy of IoT, big data analytics, and AI is set to further optimize energy production and distribution. This integration enables the development of sophisticated decision-support systems that enhance predictive maintenance, streamline operations, and facilitate dynamic risk management in volatile energy markets. The resulting systems not only improve operational efficiency but also support strategic planning at both micro and macro levels. As energy companies embrace these innovations, future research should focus on refining data fusion methodologies and assessing the economic impacts of these digital transformations, thereby ensuring sustainable growth and long-term competitiveness in the global energy landscape.  It is also necessary to cultivate a large number of scientific and technological talents with the talents required for artificial intelligence technology, which can also promote the upgrading and transformation of energy companies to high-quality industries [4].

Located also in the cloud. Cloud computing can monitor and optimize energy consumption at the production process, and eliminate the low efficiency of the energy production. It can be combined with artificial intelligence to achieve energy reduction, energy cost reduction, and energy profit program. In Industry 4.0 context, along with the big data analysis, Industry 4.0 can centrally manage data and achieve extremely high level of production efficiency and its characteristic. Traditional energy production industry is getting prepared in the world of cloud computing. It has high efficiency and flexibility. It can be associated with Industry 4.0 and contribute significantly to energy industry. The application of cloud computing can also promote the transformation of energy companies to clean energy companies, improve energy efficiency and reasonably allocate energy use, and reduce waste.

Artificial intelligence, the Internet of Things, big data analysis, and cloud computing are all key technologies in Industry 4.0. They are closely related to each other, which can enable the energy industry to communicate and cooperate, and provide a basis for the energy supply industry to achieve more efficient energy management. Their interaction and cooperation within Industry 4.0 will have a positive impact.

Industry 4.0 was proposed by Germany in 2011 to promote the intelligent transformation of the manufacturing industry. In the field of energy, it has a unique connotation and its mission is to achieve a deep transformation of the entire industrial chain and create an intelligent, integrated, efficient and sustainable energy ecosystem. Its essence is to use digital technology to break down information barriers, achieve the integration and coordinated optimization of energy, information and business flows, and at the same time focus on integration with other industries to promote innovation in energy consumption models.

In summary, the integration of cloud computing, artificial intelligence, IoT, and big data analytics under the umbrella of Industry 4.0 has the potential to revolutionize the energy industry. These technologies collectively enhance efficiency, drive innovation, and support the sustainable transformation of energy production. The future of the energy sector lies in its ability to adapt to these technological advancements, thereby achieving a seamless, digitally empowered, and environmentally responsible industrial ecosystem.