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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]

The motivation for this paper comes from the recognition that our understanding of specialisation might be too simplistic and that the dichotomy of specialisation and diversification could be outdated not reflecting the richness of real complex economic and technological relations among industries. Drawing on a qualitative study of the Hamburg Aviation (HAv) cluster, this paper discusses the peculiarities of a cluster profile in the digital time - the age of Industry 4.0 (I4.0), touching upon the issues of cluster structure and the complexity of production, synchronising specialisation with diversification, branching, and bridging, and the I4.0 attributes facilitating complementarity. The final research proposal, which is empirically embedded in the studied context, states that related variety encompassing both 'specialisation in diversification' and 'diversification within specialisation' can be further developed by a blending process. This can lead to branching and is modulated by the universal character of the I4.0 and a problem-solving attitude. It takes the form of an additive (new entries) or multiplicative (spinoffs) evolution, and, ultimately, owing to the complementarity, it can provide sustainable competitive advantages. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to show the interaction effects between clusters and cluster-specific attributes and the industrial internet of things (IoT) knowledge of a firm on the innovativeness of firms. Cluster theory and the concept of key enabling technologies are linked to test their effect on a firm's incremental and radical knowledge generation. Design/methodology/approach: Quantitative approach at the firm-level. By combining several data sources (e.g. ORBIS, PATSTAT and German subsidy catalogue) the paper relies on a unique database encompassing 8,347 firms in Germany. Ordinary least squares (OLS)-regression techniques are used for data analysis. Findings: Industrial IoT is an important driver of radical patents, mediated positively by firm size. For incremental knowledge, a substitution effect occurs between a cluster and IoT effects, which is bigger for larger firms and dependent on cluster attributes and firms' outside connections. Research limitations/implications: The paper opens up new research paths considering long-term disruptive effects of the industrial IoT compared to short-term effects on the innovativeness of firms within clusters. Additionally, it enables further research enriching the discussion about cluster attributes and how these affect ongoing processes. Practical implications: Linking cluster theory and policy with Industry 4.0 raises awareness for being considerate in terms of funding and scrutinising one-size-fits-all approaches. Originality/value: Connecting the concepts of a cluster and advanced manufacturing technologies as a proxy for industrial IoT, specifically focussing on both radical and incremental innovations is a new approach. Especially, taking into account the interaction effects between cluster attributes and the influence of industrial IoT on the innovativeness of firms. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to explore the nature of Industry 4.0 (I4.0) cluster, to establish and empirically verify in the pilot study the role of clusters in developing the fourth industrial revolution. It aims to find out if the cluster can provide a conducive knowledge environment fostering the advancement of I4.0; simplify the implementation of I4.0 by making it faster, easier, and cheaper and finally be applied as policy tool organising the development of I4.0. Design/methodology/approach: This paper is based on the narrative literature review mapping the cluster's nature with I4.0 features. It adopts the case study approach and uses simple statistical analysis to explore the basic characteristics of I4.0 clusters combined with a survey technique – short questionnaire organised in three major blocks. Findings: Drawing on German pilot study it can be confirmed that clusters offer conducive environment facilitating the emergence, testing and development of I4.0 specific solutions. They provide favourable knowledge environment, simplify and increase the efficiency of the business processes and organise the policymaking in this area. Originality/value: The results of presented pilot study rooted in Germany – a country seen as the front-runner in implementing the solutions of the fourth industrial revolution – can add a certain value to the emerging research on unearthed linkages between clusters and I4.0. This paper might be seen as a contribution to the emerging literature on the spatial dimension of I4.0. It expands previous research on cluster channels' likely impact on I4.0. [ABSTRACT FROM AUTHOR]

Fourth Industrial Revolution (4IR) technologies have elevated the capabilities and possibilities of improvement and efficiency in the energy sector. This paper interrogates how energy companies in South Africa, Germany and China apply 4IR technologies. A total of 26 energy companies in those countries were surveyed. An analysis was carried out using the Cronbach Alpha, Kruskal-Wallis and Mann-Whitney tests. Survey results indicate that 85% of companies acknowledge good levels of participation in the 4IR, and were clear about which 4IR technologies are important, although few companies develop these themselves. Technologies enabling access to big, real-time data (BRTD) and BRTD analysis software, are valued the most in measured importance, efficiency, reliability and ability to be integrated across the energy system. The transfer of data using the Internet of things ranked highly as a 4IR technology, whereas artificial intelligence, robotics and machine-human integration (also referred to as machine-human interaction) are considered less important, efficient, and reliable. China rates 4IR technologies as more important than South Africa and Germany do. For South Africa to be competitive in the global energy sector it needs to engage with and embrace 4IR technologies to a greater extent. [ABSTRACT FROM AUTHOR]

This paper contributes to the recent discussion concerning the interactions between China and Germany in the context of Industry 4.0, highlighting the most relevant innovation and trade trends and the policy implications of this collaboration. The qualitative analysis examines the features of the innovation systems in Germany and China and the strategies implemented to boost the innovation process. The quantitative analysis exploits trade, patent and publications data to identify trends related to China-Germany cooperation. The paper provides insights into the policy implications for both countries of Sino-German cooperation in relation to Industry 4.0. [ABSTRACT FROM AUTHOR]

Since 2011, the Industry 4.0 initiative is a key research and development direction towards flexible production systems in Germany. The objective of the initiative is to deal with the challenge of an increased production complexity caused by various factors such as increasing global competition between companies, product variety, and individualization to meet customer needs. For this, Industry 4.0 envisions an overarching connection of information technologies with the production process, enabling smart manufacturing. Bringing current production systems to this objective will be a long transformation process, which requires a coherent migration path. The aim of this paper is to represent an exemplary production development way towards Industry 4.0 using eminent formalization approaches and standardized automation technologies. [ABSTRACT FROM AUTHOR]

Summary: The transition to an intermittent energy production from renewable energy sources (RES) increases the complexity of providing reliable energy supply in Germany. Yet the growing number of RES impede the necessary effort to control the system. The introduction of digital or smart energy systems is often proclaimed as a logical next step towards coping with this rising complexity. It seems convenient that the manufacturing industry, as one of the major energy consumers, is currently also in a process of a digital transition, the fourth industrial revolution. This paper explores the current state of expert discourse on the role of a digitized industry as a potential enabler for the energy transition using Germany as a case study. For this purpose, we gathered qualitative data through semistructured interviews among industry managers and energy researchers. We identified the three major areas in the expert discourse of industry's future potentials: (1) increasing transparency in the energy system, (2) providing demand flexibility, and (3) increasing energy efficiency. In this paper, we address the internal barriers and explore industry's reluctance to interact with the energy system in order to initiate a transition. [ABSTRACT FROM AUTHOR]

The increased rate of technological advancements with Globalization changed, and still changing the industry structures, corporates, the way of working. In recent years Industry 4.0 became one of the prominent subjects. Therefore various corporations and research companies have contributed greatly to the literature of Industry 4.0. In order to find out the fields, countries and authors' contribution to the subject in terms of conducting studies and their influence on other studies, published studies for the last two decades are reviewed with the bibliometric analysis method. The types, key research subjects, the cross-subject relations and collaborations for 1084 document reviewed by the analysis are revealed. With a systematic map that will be created for Industry 4.0, the aim is to indicate the progress of published papers in graphics, to determine the current fields of interest regarding the subject and in turn to guide the potential future researches. Among these results, it is seen that Business and Management fields, and Engineering are the most prominent disciplines in terms of working on Industry 4.0. Germany has most publications and BRIC countries, such as China at the forefront, Brazil and Russia follow Germany closely. [ABSTRACT FROM AUTHOR]

Industry 4.0, a term invented by Wolfgang Wahlster in Germany, is celebrating its 10th anniversary in 2021. Still, the digitalization of the production environment is one of the hottest topics in the computer science departments at universities and companies. Optimization of production processes or redefinition of the production concepts is meaningful in light of the current industrial and research agendas. Both the mentioned optimization and redefinition are considered in numerous subtopics and technologies. One of the most significant topics in these areas is the newest findings and applications of artificial intelligence (AI)—machine learning (ML) and deep convolutional neural networks (DCNNs). The authors invented a method and device that supports the wiring assembly in the control cabinet production process, namely, the Wire Label Reader (WLR) industrial system. The implementation of this device was a big technical challenge. It required very advanced IT technologies, ML, image recognition, and DCNN as well. This paper focuses on an in-depth description of the underlying methodology of this device, its construction, and foremostly, the assembly industrial processes, through which this device is implemented. It was significant for the authors to validate the usability of the device within mentioned production processes and to express both advantages and challenges connected to such assembly process development. The authors noted that in-depth studies connected to the effects of AI applications in the presented area are sparse. Further, the idea of the WLR device is presented while also including results of DCNN training (with recognition results of 99.7% although challenging conditions), the device implementation in the wire assembly production process, and its users' opinions. The authors have analyzed how the WLR affects assembly process time and energy consumption, and accordingly, the advantages and challenges of the device. Among the most impressive results of the WLR implementation in the assembly process one can be mentioned—the device ensures significant process time reduction regardless of the number of characters printed on a wire. [ABSTRACT FROM AUTHOR]

• Emerging technologies can be profiled using Wikipedia pages and their links. • Graph links between Wikipedia pages represent knowledge structures. • In the German version of Wikipedia Industry 4.0 has a structurally different clustering. • The German graph of Industry 4.0 does not include the Cloud computing cluster. • Germany shapes the 4.0 paradigm as a proprietary, intra-company technology. Among emerging technologies large attention has been devoted to the so called Fourth Industrial Revolution, or Industry 4.0, which is also a case study of a major industrial policy initiative, led by Germany. In the field of methodologies to profile and monitor emerging technologies the role of Wikipedia has been recently explored. In this paper we extend the use of Wikipedia by comparing the German edition with the world largest edition (in English) in order to examine whether there are significant structural differences. We first validate the use of Wikipedia for emerging technologies and for cross-language comparisons as a tool for (almost) real time strategic analysis. We then extract all Wikipedia pages related to Industry 4.0, build up a knowledge network and study its topological properties in the two editions. We find striking differences, which can be explained with respect to the persistence of the industrial pattern of specialization of Germany with respect to all other countries. Emerging technologies introduce novelty but also preserve path-dependency in the pattern of specialization. The implications for companies and policy makers are discussed. [ABSTRACT FROM AUTHOR]

The Industry 4.0 paradigm, since its initial conception in Germany in 2011, has extended its scope and adoption to a broader set of technologies. It is being considered as the most vital mechanism in the production systems lifecycle. It is the key element in the digital transformation of manufacturing industry all over the world. This scenario imposes a set of major unprecedented challenges which require to be overcome. In order to enable integration in horizontal, vertical, and end-to-end formats, one of the most critical aspects of this digital transformation process consists of effectively coupling digital integrated service/products business models with additive manufacturing processes. This integration is based upon advanced AI-based tools for decentralized decision-making and for secure and trusted data sharing in the global value. This paper presents the FASTEN IIoT Platform, which targets to provide a flexible, configurable, and open solution. The platform acts as an interface between the shop floor and the industry 4.0 advanced applications and solutions. Examples of these efforts comprise management, forecasting, optimization, and simulation, by harmonizing the heterogeneous characteristics of the data sources involved while meeting real-time requirements. [ABSTRACT FROM AUTHOR]

Digitalization of production environment, also called Industry 4.0 (the term invented by Wahlster Wolfgang in Germany) is now one of the hottest topics in the computer science departments at universities and companies. One of the most significant topics in this area is augmented reality (AR). The interest in AR has grown especially after the introduction of the Microsoft HoloLens in 2016, which made this technology available for researchers and developers all around the world. It is divided into numerous subtopics and technologies. These wireless, see-through glasses give a very natural human-machine interface, with the possibility to present certain necessary information right in front of the user's eyes as 3D virtual objects, in parallel with the observation of the real world, and the possibility to communicate with the system by simple gestures and speech. Scientists noted that in-depth studies connected to the effects of AR applications are presently sparse. In the first part of this paper, the authors recall the research from 2019 about the new method of manual wiring support with the AR glasses. In the second part, the study (tests) for this method carried out by the research team is described. The method was applied in the actual production environment with consideration of the actual production process, which is manual wiring of the industrial enclosures (control cabinets). Finally, authors deliberate on conclusions, technology's imperfections, limitations, and future possible development of the presented solution. [ABSTRACT FROM AUTHOR]