Industry 4.0 and supply chain performance: A systematic literature review of the benefits, challenges, and critical success factors of 11 core technologies

Rad, Fakhreddin Fakhrai; Oghazi, Pejvak; Palmié, Maximilian; Chirumalla, Koteshwar; Pashkevich, Natallia; Patel, Pankaj C.; Sattari, Setayesh

doi:10.1016/j.indmarman.2022.06.009

Cited by 110 publications

(36 citation statements)

References 157 publications

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“…Segura et al [50] surveyed articles highlighting the safety concerns in human-robot systems in the smart manufacturing industries. Rad et al [51] reviewed the core technologies of industry 4.0 Journal of Robotics and Control (JRC) ISSN: 2715-5072 584 from the perspective of enhancing supply chain performance. Aravindaraj and Chinna [52] reviewed literature about advanced warehouse management in industry 4.0, with an emphasis on sustainability.…”

Section: A Related Reviewsmentioning

confidence: 99%

Robotics in Industry 4.0: A Bibliometric Analysis (2011-2022)

Sekhar

Shah²,

Iswanto

2022

Journal of Robotics and Control

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Robotics forms an integral part of industry 4.0, the industrial revolution of the 21st century. This paper presents a bibliometric analysis of Web of Science (WoS) indexed publications addressing this emerging field from 2011 till June 2022. WoS research publications were firstly analysed along multiple verticals such as annual counts, types, publishing sources, research directions, researchers, organizations, and countries. Next, co-authorship collaborations among authors, organizations, and countries were discovered. This was followed by an analysis of co-occurring keywords related to robotics in industry 4.0. Finally, a detailed citation analysis was carried out to unearth citation linkages among authors, institutions, documents, nations, and journals. Latest trends, under-investigated topics, and future directions are also discussed. Primary results indicate that more than 3000 articles are being published annually in this emerging field, with a total of 18,893 documents published in WoS during the last decade. The 'IEEE Access', Chinese Academy of Science, Wang Y. (USA), and the USA emerged as the topmost productive journal, institution, author, and nation. Porpiglia Francesco (Italy), Chinese Academy Science and USA obtained the highest co-authorship total link strength (TLS); whereas Lee Chengkuo (Singapore), China, Chinese Academy Science, and the IEEE Access scored the highest citation TLS among authors, countries, organizations, and sources respectively. Machine learning (ML) emerged as the highest co-occurring keyword, followed by artificial intelligence (AI). Computer Science emerged as the most trending research domain, followed by general applications. In the future, ML and AI will advance more sophisticated robots in industry 4.0 systems.

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Section: A Related Reviewsmentioning

confidence: 99%

Robotics in Industry 4.0: A Bibliometric Analysis (2011-2022)

Sekhar

Shah²,

Iswanto

2022

Journal of Robotics and Control

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“…To realize the visions of intelligent, reliable, and collaborative future industrial infrastructures, a significant and widespread transformation needs to happen to the existing industrial systems, their services, the applications, the business processes, and even the involved personnel [1], [2]. The first step in this process is the digitization of the provided information, which enables the assets to capture the analog world, transform it, and make it available in a digital format [3].…”

Section: Introductionmentioning

confidence: 99%

Alignment of the IEEE Industrial Agents Recommended Practice Standard With the Reference Architectures RAMI4.0, IIRA, and SGAM

Leitão¹,

Karnouskos

Strasser

et al. 2023

IEEE Open J. Ind. Electron. Soc.

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Industrial cyber-physical systems (ICPS) are a key element that acts as the backbone infrastructure for realizing innovative systems compliant with the fourth industrial revolution vision and requirements to realize it. Several architectures, such as the reference architectural model industry 4.0 (RAMI4.0), the industrial Internet reference architecture (IIRA), and the smart grid architecture model (SGAM), have been proposed to develop and integrate ICPS, their services, and applications for different domains. In such architectures, the digitization of assets and interconnection to relevant industrial processes and business services is of paramount importance. Different technological solutions have been developed that overwhelmingly focus on the integration of the assets with their cyber counterpart. In this context, the adoption of standards is crucial to enable the compatibility and interoperability of these network-based systems. Since industrial agents are seen as an enabler in realizing ICPS, this work aims to provide insights related to the use and alignment of the recently established IEEE 2660.1 recommended practice to support ICPS developers and engineers to integrate assets in the context of each one of the three referred reference architectures. A critical discussion also points out some noteworthy aspects that emerge when using the IEEE 2660.1 in these architectures and discusses limitations and challenges ahead. INDEX TERMS Standards, industrial agents, industrial cyber-physical systems (ICPS), industrial Internet of things (IIoT), reference architectural model industry 4.0 (RAMI4.0), industrial Internet reference architecture (IIRA), smart grid architecture model (SGAM).

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“…While Industry 4.0 has the potential to revolutionize traditional manufacturing processes, there are still challenges to overcome, such as economic and structural barriers [ 4 , 5 ]. Industry 4.0 can significantly impact business results, but preparation is necessary to effectively embrace the change [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Where to Place Monitoring Sensors for Improving Complex Manufacturing Systems? Discussing a Real Case in the Food Industry

Pellicer

Tungekar

Carpitella

2023

Sensors

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Industry 4.0 technologies offer manufacturing companies numerous tools to enhance their core processes, including monitoring and control. To optimize efficiency, it is crucial to effectively install monitoring sensors. This paper proposes a Multi-Criteria Decision-Making (MCDM) approach as a practical solution to the sensor placement problem in the food industry, having been applied to wine bottling line equipment at a real Italian winery. The approach helps decision-makers when discriminating within a set of alternatives based on multiple criteria. By evaluating the interconnections within the different equipment, the ideal locations of sensors are suggested, with the goal of improving the process’s performance. The results indicated that the system of electric pumps, corker, conveyor, and capper had the most influence on the other equipment which are then recommended for sensor control. Monitoring this equipment will result in the early discovery of failures, potentially also involving other dependant equipment, contributing to enhance the level of performance for the whole bottling line.

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Industry 4.0 and supply chain performance: A systematic literature review of the benefits, challenges, and critical success factors of 11 core technologies

Cited by 110 publications

References 157 publications

Robotics in Industry 4.0: A Bibliometric Analysis (2011-2022)

Robotics in Industry 4.0: A Bibliometric Analysis (2011-2022)

Alignment of the IEEE Industrial Agents Recommended Practice Standard With the Reference Architectures RAMI4.0, IIRA, and SGAM

Where to Place Monitoring Sensors for Improving Complex Manufacturing Systems? Discussing a Real Case in the Food Industry

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