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Cited by 208

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Industry 4.0 implementation for multinationals

Telukdarie, Arnesh, Buhulaiga, Eyad, Bag, Surajit, Gupta, Shivam, Luo, Zongwei·2018·Process Safety and Environmental Protection
DOI 10.1016/j.psep.2018.06.030
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Abstract

Abstract Delivering on digitalization for large multinational business, in the contemporary context of global operations and real time delivery, is a significant opportunity. Operations of localised facilities independent of global operations can result in compromised global synergies. Centralised functions such as research and development, optimisations of assets, corporate planning (strategy, investment planning, financial), and supply chain together with any other function deliver significant business value. Integration of these functions via industry 4.0 delivers significant business value, delivering strategic and operational benefits. This research proposes a global system approach, as defined by industry 4.0 (vertical, horizontal and total business integration), to this challenge, from ERP through manufacturing systems down to instrumentation. The proposed work resolves the inter-site challenges together with global standardization and inter-functional integration. This proposed architecture is reinforced by a simulation illustrating the benefits of the integrated business.

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Crossref · 10.1016/j.psep.2018.06.030

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Metadata

Authors
Telukdarie, A., Buhulaiga, E., Bag, S., Gupta, S., & Luo, Z.
Venue
Process Safety and Environmental Protection
Publisher
Elsevier BV
Published
2018-08
Volume
118
Pages
316-329
ISSN
  • 0263-8762 (ISSN-L)
  • 0957-5820
DOI
10.1016/j.psep.2018.06.030
OpenAlex
W2810880535
Cited by
208
References
3
FWCI
22.84
Type
journal article
Language
en
Open access
closed

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.