Data sharing in Industry 4.0 - AutomationML, B2MML and International Data Spaces-based solutions

Czvetkó, Tímea; Abonyi, János

doi:10.1016/j.jii.2023.100438

Cited by 5 publications

(2 citation statements)

References 33 publications

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“…Based on our results, we speculate that technology spillovers may be the essential driver of agglomeration, particularly for technology-intensive firms. Given the growing significance of information resources in the digital economy [ 74 ], serving as an irreplaceable medium for technological spillovers, enterprises can invest in digital infrastructure development, including data centers and cloud computing, to facilitate information integration by optimizing information management and sharing. Once geographical barriers for information are lifted, firms can seek better solutions through cross-regional cooperation [ 75 ] and optimizing the allocation of resources.…”

Section: Discussionmentioning

confidence: 99%

Mining co-location patterns of manufacturing firms using Q statistic and additive color mixing

Song,

Li,

Wang

et al. 2024

PLoS ONE

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The agglomeration effect significantly influences firms’ site selection. Manufacturing firms often exhibit intricate spatial co-location patterns that are indicative of agglomerations due to their reliance on material input and product output across various subdivisions of manufacture. In this study, we present an analytical approach employing the Q statistic and additive color mixing visualization to assess co-location patterns of manufacturing firms. We identified frequent pairs and triplets of manufacturing divisions, mapping them to reveal distinct categories: labor-intensive clusters, upstream/downstream industrial chains, and technology-spillover clusters. These agglomeration categories concentrate in different regions of the city. Policy implications are proposed to promote the upgrade of labor-intensive divisions, enhance the operational efficiency of upstream/downstream industrial chains, and reinforce the spillover effects of technology-intensive divisions.

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Section: Discussionmentioning

confidence: 99%

Mining co-location patterns of manufacturing firms using Q statistic and additive color mixing

Song,

Li,

Wang

et al. 2024

PLoS ONE

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“…The fourth industrial revolution was triggered mostly by the developments in information technology. Automation, introduction to robotics, big data analytics, artificial intelligence, machine learning, smart systems and Internet of Things (IoT) were mostly regarded as the enabling technologies of Industry 4.0 (Czvetkó and Abonyi, 2023; Gupta, 2023). The next industrial revolution that can transform the manufacturing and supply chains is Industry 5.0 (Di Vaio et al.…”

Section: Introductionmentioning

confidence: 99%

Industry 5.0: analyzing the challenges in implementation using grey influence analysis

Rajesh

2023

JEIM

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PurposeThe author explores the challenges to implementation of Industry 5.0 in the manufacturing sector, considering the developing economy context and studying the causal relationships among factors using an advanced causal modelling technique, the Grey Influence Analysis (GINA). The challenges were further classified based on importance and their influencing power.Design/methodology/approachThe author uses the novel causal modelling technique of GINA to study and understand the influence relations among the challenges to implementation of Industry 5.0.FindingsBased on the results from the expert response-based study in the Indian manufacturing industry, it is seen that the Regulatory challenges (RGC) appear to be the most important challenge that needs to be tackled first, while implementing Industry 5.0. Integration with existing systems and Ethical challenges (ETC) emerge as the second and third most important in the category of challenges, as per the results from the GINA analysis.Research limitations/implicationsThe RGC and the ETC need to be addressed prior to implementation and it is necessary to check whether the technologies comply with regulations and whether it creates serious job displacements. While implementation, the challenges with integration to existing systems can be appropriately tackled.Practical implicationsAs a practical implication of the study, the author suggests that a proactive and reactive approach can be adopted to implement the Industry 5.0 concepts to reality. The RGC can be viewed for the adoption of technology, integration challenges can be viewed by understanding the existing systems, and ETC can be addressed by understanding the workforce in combination with technologies.Originality/valueThe shift in focus on sustainability and resilience has transformed the conventional industries to think beyond efficiency and productivity, toward being more responsible to society. The study analyzes the challenges to implementation of Industry 5.0 and the causal relations among them considering an expert response-based study.

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Advancements in Industry 4.0 Asset Management: Interoperability and Cyber Security Challenges and Opportunities

Usmani,

Happonen,

Watada

2023

Lecture Notes in Networks and Systems

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Data sharing in Industry 4.0 - AutomationML, B2MML and International Data Spaces-based solutions

Cited by 5 publications

References 33 publications

Mining co-location patterns of manufacturing firms using Q statistic and additive color mixing

Mining co-location patterns of manufacturing firms using Q statistic and additive color mixing

Industry 5.0: analyzing the challenges in implementation using grey influence analysis

Advancements in Industry 4.0 Asset Management: Interoperability and Cyber Security Challenges and Opportunities

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