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Advances in digital factory technologies are offering great potential to innovate higher education, by enabling innovative learning approaches based on virtual laboratories that increase the involvement of students while delivering realistic experiences. This article introduces a framework for the development of virtual learning applications by addressing multidisciplinary requirements. The implementation of the framework can be eased by the use of the proposed virtual learning factory application (VLFA), an open-source solution that takes advantage of virtual reality to support innovative higher-education learning activities in industrial engineering. A complete design and development workflow is described, starting from the identification of the requirements, to the design of software modules and underlying technologies, up to the final implementation. The framework and the VLFA have been tested to implement a serious game related to the design and analysis of manufacturing systems, also collecting the feedback of students and teachers. [ABSTRACT FROM AUTHOR]

The current digital transformation in manufacturing has a strong impact on the competencies needed by manufacturing companies. This leads to evolving requirements for digital training in industrial engineering courses. The concept of virtual labs in academic environments can be instrumental in teaching new digital skills through practical experience. This paper aims to examine the requirements and essential factors involved in designing virtual labs, proposing a framework to meet the requirements of virtual lab activities, integrating didactic and research purposes while examining the requirements and essential factors involved in designing virtual labs digital twin as an enabling technology. The framework is the result of the analysis of the technical aspects related to immersive technologies, such as extended reality, together with insights gathered from interviews and pilot testing conducted in workshops involving students, teachers, and lab managers from three institutions implementing virtual labs. The outcomes of this study include the digital model of four manufacturing labs as virtual labs that are openly available for academic purposes. This showcases a commitment towards offering quality and inclusive engineering education through cutting­edge virtual technologies.

The primary objective of this research endeavor was to devise an improved workplace design tailored to the demands of a digital factory environment. With the overarching aim of enhancing efficiency and productivity, a comprehensive proposal was formulated to improve layout configurations within the designated enterprise. The key focus lies in minimizing material transit across individual workstations, thereby mitigating potential bottlenecks and streamlining operations. Employing a structured workplace research framework, this study delved into material flow analysis techniques, augmented by the utilization of visTABLE software. While visTABLE served solely to visualize the work environment effectively, it played a crucial role in validating proposed solutions. Notably, the investigation yielded a discernible reduction in beam production time, marking a significant improvement of 10 min. These findings underscored the efficacy of the proposed solutions in addressing specific operational challenges faced by the company. Furthermore, this study facilitated a deeper understanding and visualization of the processes intrinsic to the digital factory environment. Elucidating workflow procedures at the workplace enabled stakeholders to identify areas for further improvement and refinement. In doing so, the research contributed to the overall efficiency and effectiveness of operations within the digital factory, paving the way for continued improvement and innovation in the field. [ABSTRACT FROM AUTHOR]

This article explores the transformative potential of learning factories in mechatronic systems development. Learning factories offer a dynamic, collaborative environment that bridges the gap between academia and industry, creating a mutually beneficial ecosystem. The LEONARDO project aims to develop innovative teaching methods, materials and tools for human-centric industrial engineering and management education leveraging on an industry 5.0 replica of a brewing system. Brewing as a process can be considered as highly complex, while brewing as a procedure serves as a ‘sexy vehicle’ for appealing student’s interest in industry 5.0 applications and human-centric production. The brewing process is and will increasingly be more automated and highly supervised. For the latter, modern implementations of sensors such as electronic nose, electronic tongue, and infrared spectroscopy are required to be installed on the brewing equipment. To efficiently use the sensor outputs, the produced signals need to be merged locally and processed adequately, researched and investigated deeply by the authors up-front with the results to be summarized. Furthermore, to enable the physical bridging of various involved institutions across Europe, connecting the relevant sites virtually presents another technological challenge. Adequate IoT equipment needs to be selected and included in the whole setup as well. Furthermore, an emphasis needs to be made on the human-centric approach, as well as data visualization. Each of the aforementioned pieces of technology need a thorough investigation along with a decent focus in integrating the puzzle pieces into the big picture which is the brewing plant. In this paper we describe the interaction along with the system integration strategies of the listed fields to enable a future proof industry 5.0 ready brewing plant, focusing on the human-centric approach demanded in the industry5.0 feature description. [ABSTRACT FROM AUTHOR]

The current digital transformation in manufacturing has a strong impact on the competencies needed by manufacturing companies. This leads to evolving requirements for digital training in industrial engineering courses. The concept of virtual labs in academic environments can be instrumental in teaching new digital skills through practical experience. This paper aims to examine the requirements and essential factors involved in designing virtual labs, proposing a framework to meet the requirements of virtual lab activities, integrating didactic and research purposes while examining the requirements and essential factors involved in designing virtual labs digital twin as an enabling technology. The framework is the result of the analysis of the technical aspects related to immersive technologies, such as extended reality, together with insights gathered from interviews and pilot testing conducted in workshops involving students, teachers, and lab managers from three institutions implementing virtual labs. The outcomes of this study include the digital model of four manufacturing labs as virtual labs that are openly available for academic purposes. This showcases a commitment towards offering quality and inclusive engineering education through cuttingedge virtual technologies. [ABSTRACT FROM AUTHOR]

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The primary objective of this research endeavor was to devise an improved workplace design tailored to the demands of a digital factory environment. With the overarching aim of enhancing efficiency and productivity, a comprehensive proposal was formulated to improve layout configurations within the designated enterprise. The key focus lies in minimizing material transit across individual workstations, thereby mitigating potential bottlenecks and streamlining operations. Employing a structured workplace research framework, this study delved into material flow analysis techniques, augmented by the utilization of visTABLE software. While visTABLE served solely to visualize the work environment effectively, it played a crucial role in validating proposed solutions. Notably, the investigation yielded a discernible reduction in beam production time, marking a significant improvement of 10 min. These findings underscored the efficacy of the proposed solutions in addressing specific operational challenges faced by the company. Furthermore, this study facilitated a deeper understanding and visualization of the processes intrinsic to the digital factory environment. Elucidating workflow procedures at the workplace enabled stakeholders to identify areas for further improvement and refinement. In doing so, the research contributed to the overall efficiency and effectiveness of operations within the digital factory, paving the way for continued improvement and innovation in the field.

In today's industry, the fourth industrial revolution is underway, characterized by the integration of advanced technologies such as artificial intelligence, the Internet of Things, and big data. One of the key pillars of this revolution is the technology of digital twin, which is rapidly gaining importance in various industries. However, the concept of digital twins is often misunderstood or misused as a buzzword, leading to confusion in its definition and applications. This observation inspired the authors of this paper to create their own demonstration applications that allow the control of both the real and virtual systems through automatic two-way communication and mutual influence in context of digital twins. The paper aims to demonstrate the use of digital twin technology aimed at discrete manufacturing events in two case studies. In order to create the digital twins for these case studies, the authors used technologies as Unity, Game4Automation, Siemens TIA portal, and Fishertechnik models. The first case study involves the creation of a digital twin for a production line model, while the second case study involves the virtual extension of a warehouse stacker using a digital twin. These case studies will form the basis for the creation of pilot courses for Industry 4.0 education and can be further modified for the development of Industry 4.0 educational materials and technical practice. In conclusion, selected technologies are affordable, which makes the presented methodologies and educational studies accessible to a wide range of researchers and solution developers tackling the issue of digital twins, with a focus on discrete manufacturing events. [ABSTRACT FROM AUTHOR]

The main goal of every production is an optimally set and stable production process with the lowest possible costs. Such settings can only be achieved through many years of experience or very specific research, which focuses on several critical factors. An example of such factors can be the size and use of available space or the location of the production line and the logistical location of individual production sites, which is individual for each production process. Specific research can be carried out, for example, by means of the TX Plant simulation application, which was used in the present article for the production process of making fiber from pellets. The output of this research is the effective use of the so-called "Digital factory" to make the process in the already created conditions more efficient. This was achieved by the TX Plant simulation application, resulting in a reduced production time and increasing overall productivity. An intuitive interaction with factory equipment is possible with this approach, which allows users to immerse themselves in the virtual factory environment. As a result, a layout's efficiency of surface use, flow of martial, and ergonomics can be assessed in real time. This paper aims to demonstrate how virtual reality (VR) can be used to simulate a digital factory to aid in decision making and enhance factory efficiency. [ABSTRACT FROM AUTHOR]

In this paper, in order to help improve the information capacity of modern factories, a full connection digital factory for industrial Internet identity resolution is built, and digital technology is used to perform the digital interconnection of the production equipment. The full connection digital factory is an advanced factory with extensive connection of production units, deep integration of IT–OT, full release of data value, and improvement of the total factor productivity. This is enabled by the full integration and use of the new generation technologies represented by 5G, edge computing, and identity resolution to reach new factory level, workshop level, and production line level production scenarios. Based on the integration of infrastructure, information technology, and platform service resources, a full connection digital factory architecture is constructed. The fusion application of 5G, edge computing, and mark resolution technology in transformer discrete manufacturing digital plant is then discussed. The challenges and development trends are summarized. Finally, it is demonstrated that the full connection digital factory of identity resolution is a possible future development direction. [ABSTRACT FROM AUTHOR]

The numerous hierarchical architectures of 2D assemblies endow them with a new dimension to realize novel properties. From theoretical perspective, freedoms stem from in‐plane and out‐plane mechanical properties of 2D materials separately, which makes 2D materials embrace more than one "persistence length" giving rise to the diverse morphologies. However, the understanding of 3D architecture formation in 2D assemblies is still in its infancy. In fact, there is even no theoretical classification or reference to help clarify structural difference among numerous experimental obtained 2D assemblies. Based on the theoretical model composed by 2D sheets and Lennard‐Jones liquids, solution concentration dependence of 2D materials conformation is systematically studied, and a ln K behavior is uncovered that can realize the theoretical conformation prediction of 2D materials. More importantly, the digital production line (solution processing procedure) is set up toward establishing the 2D assemblies' digital factory. The obtained structures may provide a reference to 2D assemblies, which benefits the understanding of the structural difference among different experiments and even help to guide the experimental design of 2D assemblies with targeted architectures and properties. [ABSTRACT FROM AUTHOR]

Hydrogen production by the electrolysis of water using renewable energy is a key component of the energy transition toward carbon dioxide emission reduction. Therefore, electrolyzers are in increased demand and have to meet higher technical requirements. The most important component of an electrolyzer is the type of cell. The proton-exchange membrane (PEM) cell is the one that offers the most promise. Cell components and their materials are subject to volatile development conditions. In particular, various production technologies come to mind for producing assembled cells the so-called membrane electrode assembly (MEA). Currently, only small quantities are produced. To meet demand, production must be scaled up quickly. Nevertheless, high requirements are placed on the quality of the cells, since high-priced raw materials are used for PEM cells. Therefore, this paper presents a data-driven approach to assessing the appropriate production technology. First, general and specific requirements of a cell production scale-up are derived. Later, characteristics of suitable cell production technologies are extracted. By using a digital factory model, suitable for shop floor data, the basis for the conception and validation of possible production concepts is laid. [ABSTRACT FROM AUTHOR]

The advancing climate change requires a shift from conventional energy sources to renewable ones, which is accompanied by the indispensability of an efficient and sustainable storage of electrical energy. The production of lithium-ion battery cells comprises an enormous complexity, as it consists of several interlinked process steps, each with different quality requirements for the (intermediate) products and the processes itself. This complexity means that a supposedly insignificant process parameter can lead to errors and deviations in the manufactured products via complex cause-effect relationships, that are not fully known. The missing knowledge of the processes and inter-process interdependencies lead to difficulties in the setup of a suitable quality assurance in battery cell production to reduce scrap rates. Beside these potentials in planning and optimizing the process chain of the battery cell factory of tomorrow are impeded. We developed a method to build up a relevant knowledge base on cause-effect relationships for battery cell production. Expert knowledge based on experience and intuition has been collected and quantitative cause-effect relationships are established. This knowledge is used to set up the initial data acquisition, ensuring relevant data being available for analysis. Afterwards, the data analysis, that validates and extends this expert knowledge, is defined. This approach is applied to real-world use-cases including machinery and laboratory equipment in battery cell production. The electrode production is selected as the basis for validation. The found inter-relationships either validate the qualitative expert knowledge, contradict this prior knowledge or else add new insights about the battery cell electrode production process that have not been considered in the qualitative expert knowledge. Methods used include correlations and a predictive power score for non-linear interdependencies. The cause-effect relationships are constantly updated by automatically analyzing the production data of the digital factory. These identified and validated cause-effect relationships allow the planning of efficient and sustainable battery cell production and data-based process chain optimization. [ABSTRACT FROM AUTHOR]

Abstract The numerous hierarchical architectures of 2D assemblies endow them with a new dimension to realize novel properties. From theoretical perspective, freedoms stem from in‐plane and out‐plane mechanical properties of 2D materials separately, which makes 2D materials embrace more than one “persistence length” giving rise to the diverse morphologies. However, the understanding of 3D architecture formation in 2D assemblies is still in its infancy. In fact, there is even no theoretical classification or reference to help clarify structural difference among numerous experimental obtained 2D assemblies. Based on the theoretical model composed by 2D sheets and Lennard‐Jones liquids, solution concentration dependence of 2D materials conformation is systematically studied, and a ln K behavior is uncovered that can realize the theoretical conformation prediction of 2D materials. More importantly, the digital production line (solution processing procedure) is set up toward establishing the 2D assemblies’ digital factory. The obtained structures may provide a reference to 2D assemblies, which benefits the understanding of the structural difference among different experiments and even help to guide the experimental design of 2D assemblies with targeted architectures and properties.

The current trend in industry is the digitalisation of production processes using modern information and communication technologies, a trend that falls under the fourth industrial revolution, Industry 4.0. Applications that link the world of information technologies (IT) and operational technologies (OT) are in particular demand. On the basis of information from practice, it can be stated that there is a shortage of specialists in the labour market for the interconnection of PLCs with information and communication technologies (cloud, web, mobile applications, etc.) in Slovakia and neighbouring countries. However, this problem is beginning to affect other countries in Europe as well. The main objective of the work was to prepare case studies suitable for educational purposes, which would address the modelling and control of a virtual discrete-event system using a PLC program and its subsequent interfacing to a cloud application. Within the scope of the work, three case studies were prepared to demonstrate the control of discrete-event system using different programming systems and their communication with the developed cloud applications. These applications are to be used for data monitoring and emergency intervention of the discrete-event system. The characteristics of the prepared case studies, which combine operational and informational technologies, predestines them for use in the sphere of education of engineers for digitalisation of production processes. They can also be helpful in research on the creation of digital twins, which represent a type of symmetry between real and virtual systems. [ABSTRACT FROM AUTHOR]

In today’s industry, the fourth industrial revolution is underway, characterized by the integration of advanced technologies such as artificial intelligence, the Internet of Things, and big data. One of the key pillars of this revolution is the technology of digital twin, which is rapidly gaining importance in various industries. However, the concept of digital twins is often misunderstood or misused as a buzzword, leading to confusion in its definition and applications. This observation inspired the authors of this paper to create their own demonstration applications that allow the control of both the real and virtual systems through automatic two-way communication and mutual influence in context of digital twins. The paper aims to demonstrate the use of digital twin technology aimed at discrete manufacturing events in two case studies. In order to create the digital twins for these case studies, the authors used technologies as Unity, Game4Automation, Siemens TIA portal, and Fishertechnik models. The first case study involves the creation of a digital twin for a production line model, while the second case study involves the virtual extension of a warehouse stacker using a digital twin. These case studies will form the basis for the creation of pilot courses for Industry 4.0 education and can be further modified for the development of Industry 4.0 educational materials and technical practice. In conclusion, selected technologies are affordable, which makes the presented methodologies and educational studies accessible to a wide range of researchers and solution developers tackling the issue of digital twins, with a focus on discrete manufacturing events.

In this paper, in order to help improve the information capacity of modern factories, a full connection digital factory for industrial Internet identity resolution is built, and digital technology is used to perform the digital interconnection of the production equipment. The full connection digital factory is an advanced factory with extensive connection of production units, deep integration of IT–OT, full release of data value, and improvement of the total factor productivity. This is enabled by the full integration and use of the new generation technologies represented by 5G, edge computing, and identity resolution to reach new factory level, workshop level, and production line level production scenarios. Based on the integration of infrastructure, information technology, and platform service resources, a full connection digital factory architecture is constructed. The fusion application of 5G, edge computing, and mark resolution technology in transformer discrete manufacturing digital plant is then discussed. The challenges and development trends are summarized. Finally, it is demonstrated that the full connection digital factory of identity resolution is a possible future development direction.

The main goal of every production is an optimally set and stable production process with the lowest possible costs. Such settings can only be achieved through many years of experience or very specific research, which focuses on several critical factors. An example of such factors can be the size and use of available space or the location of the production line and the logistical location of individual production sites, which is individual for each production process. Specific research can be carried out, for example, by means of the TX Plant simulation application, which was used in the present article for the production process of making fiber from pellets. The output of this research is the effective use of the so-called “Digital factory” to make the process in the already created conditions more efficient. This was achieved by the TX Plant simulation application, resulting in a reduced production time and increasing overall productivity. An intuitive interaction with factory equipment is possible with this approach, which allows users to immerse themselves in the virtual factory environment. As a result, a layout’s efficiency of surface use, flow of martial, and ergonomics can be assessed in real time. This paper aims to demonstrate how virtual reality (VR) can be used to simulate a digital factory to aid in decision making and enhance factory efficiency.

This article presents the results of research with the main goal of identifying possible applications of edge computing (EC) in industry. This study used the methodology of systematic literature review and text mining analysis. The main findings showed that the primary goal of EC is to reduce the time required to transfer large amounts of data. With the ability to analyze data at the edge, it is possible to obtain immediate feedback and use it in the decision-making process. However, the implementation of EC requires investments not only in infrastructure, but also in the development of employee knowledge related to modern computing methods based on artificial intelligence. As the results of the analyses showed, great importance is also attached to energy consumption, both in ongoing production processes and for the purposes of data transmission and analysis. This paper also highlights problems related to quality management. Based on the analyses, we indicate further research directions for the application of edge computing and associated technologies that are required in the area of intelligent resource scheduling (for flexible production systems and autonomous systems), anomaly detection and resulting decision making, data analysis and transfer, knowledge management (for smart designing), and simulations (for autonomous systems). [ABSTRACT FROM AUTHOR]

Sustainability is a necessity in today’s business since long-term development cannot be achieved without embracing it. The fourth industrial revolution (i.e., Industry 4.0) that introduced the digital transformation of companies is pushing the industry towards sustainable development. Human resource management (HRM), as part of the Industry 4.0 concept, plays an essential role in the process of digital transformation, since employees represent the most flexible part of the production system. This paper aims to analyze the relationship between the implementation of HRM practices and the introduction of digital technologies in manufacturing firms. Additionally, the authors intend to determine whether the introduction of digital technologies enables the flexibility of the production system. For this purpose, data gathered through the European Manufacturing Survey (EMS) are used. The analyses are based on descriptive statistics and regression analysis. The results reveal that there is a significant positive relationship between the use of HRM practices and the implementation of digital technologies in manufacturing firms. Furthermore, firms that implemented digital technologies have a tendency to organize their production processes in a way that corresponds to trends in production imposed by the Industry 4.0 concept.

Cyber-physical systems are hybrid networked cyber and engineered physical elements that record data (e.g. using sensors), analyse them using connected services, influence physical processes and interact with human actors using multi-channel interfaces. Examples of CPS interacting with humans in industrial production environments are the so-called cyber-physical production systems (CPPS), where operators supervise the industrial machines, according to the human-in-the-loop paradigm. In this scenario, research challenges for implementing CPPS resilience, promptly reacting to faults, concern: (i) the complex structure of CPPS, which cannot be addressed as a monolithic system, but as a dynamic ecosystem of single CPS interacting and influencing each other; (ii) the volume, velocity and variety of data (Big Data) on which resilience is based, which call for novel methods and techniques to ensure recovery procedures; (iii) the involvement of human factors in these systems. In this paper, we address the design of resilient cyber-physical production systems (R-CPPS) in digital factories by facing these challenges. Specifically, each component of the R-CPPS is modelled as a smart machine, that is, a cyber-physical system equipped with a set of recovery services, a Sensor Data API used to collect sensor data acquired from the physical side for monitoring the component behaviour, and an operator interface for displaying detected anomalous conditions and notifying necessary recovery actions to on-field operators. A context-based mediator, at shop floor level, is in charge of ensuring resilience by gathering data from the CPPS, selecting the proper recovery actions and invoking corresponding recovery services on the target CPS. Finally, data summarisation and relevance evaluation techniques are used for supporting the identification of anomalous conditions in the presence of high volume and velocity of data collected through the Sensor Data API. The approach is validated in a food industry real case study. [ABSTRACT FROM AUTHOR]

The technological advancements promote the rise of the fourth industrial revolution, where key terms are efficiency, innovation, and enterprises' digitalization. Market globalization, product mass customization, and more complex products need to reflect on changing the actual design methods and developing business processes and methodologies that have to be data-driven, AI-assisted, smart, and service-oriented. Therefore, there is a great interest in experimenting with emerging technologies and evaluating how they impact the actual business processes. This paper reports a comparison among the major trends in the digitalization of a Factory of the Future, in conjunction with the two major strategic programs of Industry 4.0 and China 2025. We have focused on these two programs because we have had experience with them in the context of the FIRST H2020 project. European industrialists identify the radical change in the traditional manufacturing production process as the rise of Industry 4.0. Conversely, China mainland launched its strategic plan in China 2025 to promote smart manufacturing to digitalize traditional manufacturing processes. The main contribution of this review paper is to report about a study, conducted and part of the aforementioned FIRST project, which aimed to investigate major trends in applying for both programs in terms of technologies and their applications for the factory's digitalization. In particular, our analysis consists of the comparison between Digital Factory, Virtual Factory, Smart Manufacturing, and Cloud Manufacturing. We analyzed their essential characteristics, the operational boundaries, the employed technologies, and the interoperability offered at each factory level for each paradigm. Based on this analysis, we report the building blocks in terms of essential technologies required to develop the next generation of a factory of the future, as well as some of the interoperability challenges at a different scale, for enabling inter-factories communications between heterogeneous entities. [ABSTRACT FROM AUTHOR]

The global trend in manufacturing has shifted from a manufacturing-centric process toward a user-centric process. This has resulted in a shorter lifespan and a high product replacement rate of any consumer product. Germany has introduced the concept of Industry Revolution 4.0 (IR 4.0) to convert manufacturing processes and mechanisms into cyber-physical systems (CPS). Digital factory, being the first step into CPS and IR4.0, is being targeted as the most important evolution of the manufacturing industry. This paper defines digital factories and their differences between other similar domains such as smart factories, CPS, and virtual factories. The requirements and goals of a digital factory are explained in detail to facilitate future digital factory tool developments. Furthermore, the current challenges faced in the implementation of the digital factory are proposed to be approached by adapting an interoperable virtual reality technology. This paper emphasizes the usage of virtual reality (VR) in simulating a digital factory that aids in the decision-making and efficient operation of a manufacturing facility. Furthermore, recommendations gathered from previous studies for developing VR-based digital factory tools are also explained in detail in this paper. [ABSTRACT FROM AUTHOR]

Russian companies are actively involved in the digital transformation. The key technologies and potential effects are defined, a lot of pilots and prototypes are successfully launched. The next logical step is to scale the concept from the level of individual processes to the level of assets, functions, holding companies and the whole enterprise. In the article, two main approaches to the formation of a strategic digital transformation programs are analyzed: an approach based on scaling of digital tools and an approach based on complex processes transformation. Both these approaches are aimed at increasing the level of digital maturity.

The current trend in industry is the digitalisation of production processes using modern information and communication technologies, a trend that falls under the fourth industrial revolution, Industry 4.0. Applications that link the world of information technologies (IT) and operational technologies (OT) are in particular demand. On the basis of information from practice, it can be stated that there is a shortage of specialists in the labour market for the interconnection of PLCs with information and communication technologies (cloud, web, mobile applications, etc.) in Slovakia and neighbouring countries. However, this problem is beginning to affect other countries in Europe as well. The main objective of the work was to prepare case studies suitable for educational purposes, which would address the modelling and control of a virtual discrete-event system using a PLC program and its subsequent interfacing to a cloud application. Within the scope of the work, three case studies were prepared to demonstrate the control of discrete-event system using different programming systems and their communication with the developed cloud applications. These applications are to be used for data monitoring and emergency intervention of the discrete-event system. The characteristics of the prepared case studies, which combine operational and informational technologies, predestines them for use in the sphere of education of engineers for digitalisation of production processes. They can also be helpful in research on the creation of digital twins, which represent a type of symmetry between real and virtual systems.

Game engines are middleware that allows the integration of multiple resources turning them into assets with graphic information, programmed content and physical simulation parameters. These features meet the requirements for modelling, visualizing, simulating and controlling complex production systems. Therefore, an approach based on game engines to manage the user-perceived complexity was proposed. This paper compares 24 game engines and identifies suitable modelling environments for production based on their technical and market-development features. Then, a modular machine was integrated in two game engines. The results of scopes and limitations regarding functionality, scale, physics simulation accurateness, resource redundancies and visualization are presented. [ABSTRACT FROM AUTHOR]

This article presents the results of research with the main goal of identifying possible applications of edge computing (EC) in industry. This study used the methodology of systematic literature review and text mining analysis. The main findings showed that the primary goal of EC is to reduce the time required to transfer large amounts of data. With the ability to analyze data at the edge, it is possible to obtain immediate feedback and use it in the decision-making process. However, the implementation of EC requires investments not only in infrastructure, but also in the development of employee knowledge related to modern computing methods based on artificial intelligence. As the results of the analyses showed, great importance is also attached to energy consumption, both in ongoing production processes and for the purposes of data transmission and analysis. This paper also highlights problems related to quality management. Based on the analyses, we indicate further research directions for the application of edge computing and associated technologies that are required in the area of intelligent resource scheduling (for flexible production systems and autonomous systems), anomaly detection and resulting decision making, data analysis and transfer, knowledge management (for smart designing), and simulations (for autonomous systems).

The key stage of the company's transition to Industry 4.0. It is the Digital factory development stage. The first part of the article discusses in detail the components of digital factories, the expected effects of digitalization of production and related functions, as well as the transition from strategic initiatives to the operational level – the level of business processes that are transformed under the influence of new technologies. The second part of the article describes the methodology of case studies of Russian and foreign companies that are at the forefront of changes. The third part presents the cases of manufacturing companies that have achieved significant results in the field of digital transformation, in particular, Siemens, SIBUR and Novolipetsk metallurgical combine.

The first attempts to create devices that allow interacting with the imitated reality, as well as augmenting reality with superimposed information, were made at the beginning of the 20th century, the very concept of mixed reality (the “reality-virtuality continuum”), which elements are virtual (VR) and augmented (AR) reality, is quite young (24 years), as well as the market of these technologies. The concept of virtual and augmented reality hasn’t changed radically in the past 30 years, but VR and AR devices and software, and content have gone through a significant evolutionary path, and have already experienced several growth spikes.VR and AR technologies can be applied not only in entertainment and games. Many experts believe that virtual and augmented reality, along with Big Data, cloud technologies, artificial intelligence and some others, will become the key technologies of the 4th industrial revolution. VR and AR also have the potential to become the next big computing platform. Today VR and AR technologies help not only to create conceptually new markets, but also to disrupt existing ones.This article discusses the evolution of the VR and AR concepts and technologies and current market trends. The results of the survey show the key obstacles for the mass distribution of AR and VR technologies: high implementation and operational costs of AR/VR solutions; lack of high-quality content and imperfect devices, implicit effectiveness of their use.Based on the empirical study, a rather extensive list of benefits from using virtual and augmented reality technologies has been drawn up: faster and cheaper learning, training and guiding processes, increase in their efficiency, the reduction of the costs of elements and supplies needed, training support personnel; reducing potential risks to life and health of employees and other people while special training (medical operations and invasive procedures, evacuation, security, rescue in various emergencies) and the related optimization of the compensations; reducing the number of errors and accelerating the processes of assembling, repairing and operating special equipment, searching for information, necessary details, product location in the warehouse; significant reduction of accidents rate, as well as the exploration costs, due to the early identification of malfunctions; accelerating the pace of the designing and prototyping objects, significantly reducing the cost and duration of physical modeling process; improving customer experience, product and trading platforms design, that leads to corresponding increase in volume of sales; improving (simplifying) of communication and increasing its effectiveness.

The electric motor production of the automotive industry faces numerous challenges due to weak sales and uncertain sales forecasts of the electric vehicle. To meet these challenges, scalable production systems have increasingly been set up. The application of virtual commissioning to scalable production systems holds increased potential since the deterministic simulation model can be improved step by step through the inclusion of real data. Therefore, a concrete process model is to be created describing how virtual commissioning can be made even more effective through real data connection. The validation is carried out on an application from material handling technology. [ABSTRACT FROM AUTHOR]

Flexibility and versatility in production put high demands on the planning, simulation and ramp-up of assembly systems and processes. For this purpose, a digital twin of a laser-based assembly assistance system for manual mounting tasks was developed, implemented and analyzed. A capability model was elaborated using quantitative and qualitative studies. The capability model was realized as a Unity 3D model. In the augmented reality implementation using the Microsoft HoloLens users can control the digital twin through hand gestures and voice control. The implementation shows that the digital twin of the laser-based assembly assistance supports the planning, simulation and training of employees at the shop floor. [ABSTRACT FROM AUTHOR]

The use of material flow simulation in production allows early testing of production scenarios, thus reducing overall time for production planning. However, initial modelling introduces additional expenses. One way to reduce these expenses is the use of reusable standard modules. This paper presents a method for the identification and specification of standard modules in production in order to reuse them in different material flow simulation models. The method uses company internal hypotheses about existing modules for the identification of standard modules. For the specification, the method provides a set of models, which serve as a basis for the implementation of the standard modules in a material flow simulation. The concept is demonstrated with an application example. [ABSTRACT FROM AUTHOR]

The industrial sector is the world's second largest emitter of greenhouse gases, hence a methodology for decarbonizing factory systems is crucial for achieving global climate goals. Hydrogen is an important medium for the transition towards carbon neutral factories due to its broad applicability within the factory, including its use in electricity and heat generation and as a process gas or fuel. One of the main challenges is the identification of economically and environmentally suitable design scenarios, such as for the entire value chain for hydrogen generation and application. For example, the infrastructure for renewable electricity, hydrogen generation, hydrogen conversion (e.g. into synthetic fuels), storage and transport systems as well as application in the factory. Due to the high volatility of energy generation and the related dynamic interdependencies within a factory system, a valid technical, economic and environmental evaluation of benefits induced by hydrogen technologies can only be achieved using digital factory models. In this paper, we present a framework to integrate hydrogen technologies into factory systems. This enables decision makers to identify promising measures according to their expected impact and collect data for appropriate factory modelling. Furthermore, a concept for factory modelling and simulation is presented and demonstrated in a case study from the electronics industry, assessing the use of hydrogen for decentralized power and heat generation. [ABSTRACT FROM AUTHOR]

Sustainability is a necessity in today's business since long-term development cannot be achieved without embracing it. The fourth industrial revolution (i.e., Industry 4.0) that introduced the digital transformation of companies is pushing the industry towards sustainable development. Human resource management (HRM), as part of the Industry 4.0 concept, plays an essential role in the process of digital transformation, since employees represent the most flexible part of the production system. This paper aims to analyze the relationship between the implementation of HRM practices and the introduction of digital technologies in manufacturing firms. Additionally, the authors intend to determine whether the introduction of digital technologies enables the flexibility of the production system. For this purpose, data gathered through the European Manufacturing Survey (EMS) are used. The analyses are based on descriptive statistics and regression analysis. The results reveal that there is a significant positive relationship between the use of HRM practices and the implementation of digital technologies in manufacturing firms. Furthermore, firms that implemented digital technologies have a tendency to organize their production processes in a way that corresponds to trends in production imposed by the Industry 4.0 concept. [ABSTRACT FROM AUTHOR]

Due to the emission scandals and politics the automotive industry is forced to focus more on electromobility. Along with electromobility comes the risk of a volatile consumer market, which the motor industry tries to minimize by implementing scalable production systems. This paper aims to provide a solution to support the planning of scalable production systems by using the virtual method virtual reality (VR). To achieve this goal, a model for the holistic integration of VR into the production planning process of scalable production systems is developed and different possibilities of implementation are compared and evaluated. [ABSTRACT FROM AUTHOR]

Individualization is a common trend in many fields of production across the industries. Also in the food sector, significant changes can be observed. For many products, individual offerings towards the customer are meanwhile either mandatory or at least help to increase the sales and revenue. Somehow, individual product design and production contradicts scaling effects, which are especially important for food production. On the other hand, as digitalization is implemented in a fairly limited way in the food sector, currently great chances can be observed to build a unique selling proposition and consequently gain market share by implementing appropriate measures to enable a digital food factory. This is where the proposed idea comes into the game. The starting point is the idea to produce individually developed beer and ship it to the individual customer. The beer can be designed on a web page based on typical parameters, like beer type, bitterness, colour, or alcohol concentration. In an expert mode, individual beer creations may be thoughtful, allowing the creation of completely individual recipes (for sure, not guaranteeing the customer a perfect drinking experience). In any way, the data from the web page is directly fed to the brewing equipment in the brewing facility. There, using newly to be developed specialized machines, the individually ordered beer will be produced automatically. In this paper we discuss the individual challenges at each point in the production cycles and propose solutions to those. [ABSTRACT FROM AUTHOR]

The technological advancements promote the rise of the fourth industrial revolution, where key terms are efficiency, innovation, and enterprises’ digitalization. Market globalization, product mass customization, and more complex products need to reflect on changing the actual design methods and developing business processes and methodologies that have to be data-driven, AI-assisted, smart, and service-oriented. Therefore, there is a great interest in experimenting with emerging technologies and evaluating how they impact the actual business processes. This paper reports a comparison among the major trends in the digitalization of a Factory of the Future, in conjunction with the two major strategic programs of Industry 4.0 and China 2025. We have focused on these two programs because we have had experience with them in the context of the FIRST H2020 project. European industrialists identify the radical change in the traditional manufacturing production process as the rise of Industry 4.0. Conversely, China mainland launched its strategic plan in China 2025 to promote smart manufacturing to digitalize traditional manufacturing processes. The main contribution of this review paper is to report about a study, conducted and part of the aforementioned FIRST project, which aimed to investigate major trends in applying for both programs in terms of technologies and their applications for the factory’s digitalization. In particular, our analysis consists of the comparison between Digital Factory, Virtual Factory, Smart Manufacturing, and Cloud Manufacturing. We analyzed their essential characteristics, the operational boundaries, the employed technologies, and the interoperability offered at each factory level for each paradigm. Based on this analysis, we report the building blocks in terms of essential technologies required to develop the next generation of a factory of the future, as well as some of the interoperability challenges at a different scale, for enabling inter-factories communications between heterogeneous entities.

The paper highlights events of manufacturing’s evolution and metamorphosis over a period of 60 years (as noted by the first author) and offers some observations on key developments and activities. It includes the reflections of professional activities of the first author and discussions of how manufacturing is evolving to accommodate the current and expected trends in manufacturing technology. Three specific software environments relative to developments in the design-to-manufacturing cycle are described. These lead into a perspective of what may now lie ahead, relative to enterprise issues, human system interactions, and the fully integrated “digital factory.”

Current requirements which are connected with designing new, or reali-zing the existing production systems, cause continuous and rapid changes in products and processes. This means that classical approaches of pro-duction systems design have to be extended by advanced technologies and methods, such as digital factory, virtual and augmented reality, computer simulation, reverse engineering, etc. The article describes new computer technologies, which were applied in production practice, with a particular focus on the augmented reality technology.

In the current trend of smart manufacturing, the architecture of smart manufacturing is gradually proposed by many countries in the world. Main components, elements, functions, and relationships of these smart manufacturing architectures have been clarified. However, the specific details of cross matching of different dimensions in these smart manufacturing architectures have not been thoroughly developed. Therefore, a certain part of a plane intersected of system hierarchy dimension and smart characteristics dimension in the model for smart manufacturing (SMS) from a perspective of implementation was selected for detailed study, which is defined as smart manufacturing implementation system (SMIS). Firstly, a top-level scenario planning of SMIS was proposed from perspectives of lean factory, interconnection factory, information factory, transparent factory, virtual factory, and smart factory. Then, an overall framework of SMIS was deduced through a top-level scenario planning of SMIS. Finally, through a case study, the specific implementation process of SMIS is obtained. Through the proposed overall framework and implementation path of SMIS, enterprises can implement intelligent manufacturing step by step. In addition, the top-level scenario planning and overall framework of SMIS are complementary to the SMS proposed by China. [ABSTRACT FROM AUTHOR]

In the tide of smart manufacturing in the world, many countries have put forward their own reference frameworks for smart manufacturing system. Based on the framework of smart manufacturing system (SMS) proposed by China, a reference smart manufacturing integration system (SMIS) from multi-level and multi-perspective was proposed. The reference model of SMIS was analyzed by means of system engineering. Based on this model, the overall architecture of SMIS was proposed. Then, the physics subsystem, information integration subsystem, network integration subsystem, data integration subsystem, and visualization integration subsystem for SMIS were proposed through the overall architecture of SMIS. Finally, the above integrated subsystems were collected together to deduce the implementation path of SMIS. Four reference subsystems for SMIS proposed in this paper have achieved good effects in the projects we participated in, which were organized by the state. The research results of this paper can be used as a reference for industry and government to design, set, and carry out SMIS. At the same time, it has a certain reference value for the improvement and supplement of national smart manufacturing system architecture. [ABSTRACT FROM AUTHOR]

Digitalization of manufacturing is once again on the industry application research agenda and Digital Manufacturing plays a fundamental role in this process. However, there is a lack of commonality in the literature about the purpose of Digital Manufacturing. The purpose of this paper is to analyze the concept and application domain of Digital Manufacturing considering the increasingly established Industry 4.0 paradigm. Based on a content analysis concepts are framed, and new technological characteristics identified. The paper contributes to a better understanding of the future challenges that companies face by positioning Digital Manufacturing conceptually and delimiting its application domain. [ABSTRACT FROM AUTHOR]

Taking smart manufacturing as a strategy for industrial development, China has put forward a people-oriented policy and launched a series of plans for smart manufacturing talent education (SMTE). The demand for smart manufacturing talents in ten priority areas and the industrial applications in China is very huge. Therefore, in this paper, a reference system of SMTE in China is presented, which includes discipline system, training system, practice system, and assessment system. In order to further refine the architecture of smart manufacturing system, a reference course system was proposed; the system contains seven layers, which are basic layer, technique layer, implementation layer, management layer, platform layer, application layer, and industrialization layer. Finally, nine stakeholders of the common operation body were investigated, and a reference implementation of SMTE in China was put forward. In this paper, the smart manufacturing talent education reference system, reference model, and related reference subsystems can be a very useful guideline for Chinese industry and education to design, set, and carry out the smart manufacturing talent education system. At the same time, the system has its reference value for the improvement of China's smart manufacturing system architecture. [ABSTRACT FROM AUTHOR]

Abstract Within product development process data and information management is an essential task. Data and information are generated at every stage of this process and stored in software tools used to generate that data. For large scale manufacturing systems this leads to manual work, which is error-prone. This issue intensifies due to increasing influence of computer science on those systems (e.g. Industrie 4.0), leading to a rise of complexity. New approaches are needed for a better information flow. This contribution introduces an approach of an evolving Digital Factory containing and visualizing all generated information based on an open standard meta model. [ABSTRACT FROM AUTHOR]

One of the new challenges of the 21st century is the Industry 4.0. Manufacturing companies moving away from mass production and getting closer to customized production and manufacturing of customized products through digitization. The expectations are high, meeting the requirements is a real challenge to industrial partners. In order to help meet the challenges the University of Pannonia Nagykanizsa Campus started to establish a fully automatized industrial laboratory. In this paper the architecture of the Industry 4.0 laboratory and the purpose of the Factory Subsystem is presented. [ABSTRACT FROM AUTHOR]

The 3D modelling of indoor environments and the generation of process simulations play an important role in factory and assembly planning. In brownfield planning cases, existing data are often outdated and incomplete especially for older plants, which were mostly planned in 2D. Thus, current environment models cannot be generated directly on the basis of existing data and a holistic approach on how to build such a factory model in a highly automated fashion is mostly non-existent. Major steps in generating an environment model of a production plant include data collection, data pre-processing and object identification as well as pose estimation. In this work, we elaborate on a methodical modelling approach, which starts with the digitalization of large-scale indoor environments and ends with the generation of a static environment or simulation model. The object identification step is realized using a Bayesian neural network capable of point cloud segmentation. We elaborate on the impact of the uncertainty information estimated by a Bayesian segmentation framework on the accuracy of the generated environment model. The steps of data collection and point cloud segmentation as well as the resulting model accuracy are evaluated on a real-world data set collected at the assembly line of a large-scale automotive production plant. The Bayesian segmentation network clearly surpasses the performance of the frequentist baseline and allows us to considerably increase the accuracy of the model placement in a simulation scene.