Ten Most Cited Papers in the Area of Industry 4.0 – 07 March 2017
- A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems
- Cyber-physical production systems: Roots, expectations and R&D challenges
- Service innovation and smart analytics for Industry 4.0 and big data environment
- Industry 4.0
- Human-machine-interaction in the industry 4.0 era
- Smart factories in Industry 4.0: A review of the concept and of energy management approached in production based on the Internet of Things paradigm
- Wireless requirements and challenges in Industry 4.0
- Virtual engineering object (VEO): Toward experience-based design and manufacturing for industry 4.0
- Change through digitization—value creation in the age of industry 4.0
- Global Footprint Design based on genetic algorithms – An “industry 4.0” perspective
Lee, J., Bagheri, B., & Kao, H. A. (2015). A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manufacturing Letters, 3, 18-23. DOI: 10.1016/j.mfglet.2014.12.001. (Citations: 131)
ABSTRACT: Recent advances in manufacturing industry has paved way for a systematical deployment of Cyber-Physical Systems (CPS), within which information from all related perspectives is closely monitored and synchronized between the physical factory floor and the cyber computational space. Moreover, by utilizing advanced information analytics, networked machines will be able to perform more efficiently, collaboratively and resiliently. Such trend is transforming manufacturing industry to the next generation, namely Industry 4.0. At this early development phase, there is an urgent need for a clear definition of CPS. In this paper, a unified 5-level architecture is proposed as a guideline for implementation of CPS.
Monostori, L. (2014). Cyber-physical production systems: Roots, expectations and R&D challenges. Procedia CIRP, 17, 9-13. DOI: 10.1016/j.procir.2014.03.115. (Citations: 68)
ABSTRACT: One of the most significant directions in the development of computer science and information and communication technologies is represented by Cyber-Physical Systems (CPSs) which are systems of collaborating computational entities which are in intensive connection with the surrounding physical world and its on-going processes, providing and using, at the same time, data-accessing and data-processing services available on the internet. Cyber-Physical Production Systems (CPPSs), relying on the newest and foreseeable further developments of computer science, information and communication technologies on the one hand, and of manufacturing science and technology, on the other, may lead to the 4th Industrial Revolution, frequently noted as Industry 4.0. The key-note will underline that there are significant roots generally– and particularly in the CIRP community – which point towards CPPSs. Expectations and the related new R&D challenges will be outlined.
Lee, J., Kao, H. A., & Yang, S. (2014). Service innovation and smart analytics for industry 4.0 and big data environment. DOI: 10.1016/j.procir.2014.02.001. Procedia Cirp, 16, 3-8. (Citations: 66)
ABSTRACT: Today, in an Industry 4.0 factory, machines are connected as a collaborative community. Such evolution requires the utilization of advance prediction tools, so that data can be systematically processed into information to explain uncertainties, and thereby make more “informed” decisions. Cyber-Physical System-based manufacturing and service innovations are two inevitable trends and challenges for manufacturing industries. This paper addresses the trends of manufacturing service transformation in big data environment, as well as the readiness of smart predictive informatics tools to manage big data, thereby achieving transparency and productivity.
Lasi, H, Fettke, P, Kemper, Hans-Georg, Feld, T and Hoffmann, M. Industry 4.0. Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, 2014, 6, issue 4, p. 239-242. DOI 10.1007/s12599-014-0334-4. (Citations: 47)
SUMMARY: First, the term “Industry 4.0” describes different – primarily IT driven – changes in manufacturing systems. These developments do not only have technological but furthermore versatile organizational implications. As a result, a change from product- to service-orientation even in traditional industries is expected. Second, an appearance of new types of enterprises can be anticipated which adopt new specific roles within the manufacturing process resp. the value-creation networks (Scheer 2012). For instance it is possible that, comparable to brokers and clearing-points in the branch of financial services, analog types of enterprises will also appear within the industry. With the planning, analysis, modeling, design, implementation and the maintenance (in short: the development) of such highly complex, dynamic, and integrated information systems, an attractive and at the same time challenging task for the academic discipline of BISE arises, which can secure and further develop the competitiveness of industrial enterprises.
Gorecky, D., Schmitt, M., Loskyll, M., & Zühlke, D. (2014, July). Human-machine-interaction in the industry 4.0 era. In Industrial Informatics (INDIN), 2014 12th IEEE International Conference on (pp. 289-294). IEEE. DOI: 10.1109/INDIN.2014.6945523. (Citations: 33)
ABSTRACT: The development of Industry 4.0 will be accompanied by changing tasks and demands for the human in the factory. As the most flexible entity in cyber-physical production systems, workers will be faced with a large variety of jobs ranging from specification and monitoring to verification of production strategies. Through technological support it is guaranteed that workers can realize their full potential and adopt the role of strategic decision-makers and flexible problem-solvers. The use of established interaction technologies and metaphors from the consumer goods market seems to be promising. This paper demonstrates solutions for the technological assistance of workers, which implement the representation of a cyber-physical world and the therein occurring interactions in the form of intelligent user interfaces. Besides technological means, the paper points out the requirement for adequate qualification strategies, which will create the required, inter-disciplinary understanding for Industry 4.0.
Shrouf, F., Ordieres, J., & Miragliotta, G. (2014, December). Smart factories in Industry 4.0: A review of the concept and of energy management approached in production based on the Internet of Things paradigm. In Industrial Engineering and Engineering Management (IEEM), 2014 IEEE International Conference on (pp. 697-701). IEEE. DOI: 10.1109/IEEM.2014.7058728. (Citations: 15)
ABSTRACT: The real and the virtual worlds are growing speedily and closely to form the Internet of Things (IoT). In fact, IoT has stimulated the factories and the governments to launch an evolutionary journey toward the fourth industrial revolution called Industry 4.0. Industrial production of the new era will be highly flexible in production volume and customization, extensive integration between customers, companies, and suppliers, and above all sustainable. Reviewing and analyzing the current initiatives and related studies of the smart factories/Industry 4.0, this paper presents a reference architecture for IoT-based smart factories, defines the main characteristics of such factories with a focus on the sustainability perspectives. And then it proposes an approach for energy management in smart factories based on the IoT paradigm: a guideline and expected benefits are discussed and presented.
Varghese, A., & Tandur, D. (2014, November). Wireless requirements and challenges in Industry 4.0. In Contemporary Computing and Informatics (IC3I), 2014 International Conference on (pp. 634-638). IEEE. DOI: 10.1109/IC3I.2014.7019732. (Citations: 13)
ABSTRACT: The next generation of industrial advancement which is referred as Industry 4.0 aims to inter-connect and computerize the traditional industrys such as manufacturing. The objective in Industry 4.0 is to make the factories smart enough in terms of improved adaptability, resource efficiency as well as the improved integration of supply and demand processes between the factories. Wireless communication will play a key role in enabling the Industry 4.0 systems and technologies. In this paper we focus the discussion on some of the key wireless communication challenges that will need to be met for the Industry 4.0 era. We look at how the 5th generation of communication standard may address these requirements. For machine to machine communication the three main design criterions that can be considered are latency, longevity and the reliability of communication. We take an example of WiFi communication, and benchmark it against the requirements, so as to emphasize the improvements required in wireless protocols.
Shafiq, S. I., Sanin, C., Toro, C., & Szczerbicki, E. (2015). Virtual engineering object (VEO): toward experience-based design and manufacturing for Industry 4.0. Cybernetics and Systems, 46(1-2), 35-50. DOI:10.1080/01969722.2015.1007734. (Citations: 11)
ABSTRACT: In this article we propose the concept, its framework, and implementation methodology for Virtual Engineering Objects (VEO). A VEO is the knowledge representation of an engineering object that embodies its associated knowledge and experience. A VEO is capable of adding, storing, improving, and sharing knowledge through experience. Moreover, it is demonstrated that VEO is a specialization of a Cyber-Physical System (CPS). In this article, it is shown through test models how the concept of VEO can be implemented with the Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA). The test model confirmed that the concept of VEO is able to capture and reuse the experience of engineering artifacts, which can be beneficial for efficient decision-making in industrial design and manufacturing.
Kagermann, H. (2015). Change through digitization—Value creation in the age of Industry 4.0. In Management of permanent change (pp. 23-45). Springer Fachmedien Wiesbaden. DOI:10.1007/2F978-3-658-05014-6_2. (Citations: 11)
ABSTRACT: Digitization—the continuing convergence of the real and the virtual worlds will be the main driver of innovation and change in all sectors of our economy. The exponentially growing amount of data and the convergence of different affordable technologies that came along with the definite establishment of Information and Communication Technology are transforming all areas of the economy. In Germany, the Internet of Things, Data and Services plays a vital role in mastering the energy transformation, in developing a sustainable mobility and logistics sector, in providing enhanced health care and in securing a competitive position for the leading manufacturing industry. This article discusses the impact, challenges and opportunities of digitization and concludes with examples of recommended policy action. The two key instruments for enhanced value creation in the Age of Industrie 4.0 are platform-based cooperation and a dual innovation strategy.
Schuh, G., Potente, T., Varandani, R., & Schmitz, T. (2014). Global Footprint Design based on genetic algorithms–An “Industry 4.0” perspective. CIRP Annals-Manufacturing Technology, 63(1), 433-436. DOI:10.1016/j.cirp.2014.03.121. (Citations: 11)
ABSTRACT: A cost-optimized design of a global production network is a complex task. Several optimization tools exist that determine cost-minimized solutions for defined points of times in the future but often do not take into account the development of the network over time. The approach of this article is to analyze a series of different cost-optimized scenarios for several points of time in the future with distinct parameter settings and compare its network structures. The goal of such broad calculations of future scenarios according to the idea of “Industry 4.0” is to identify a path in the trade-off between the costs for migrating a network structure into another one and the total landed costs of the regarded series of future network scenarios. The approach will be validated using data from real industrial case studies.
Note: Data Source: Scopus; Date: 07 March 2017