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Artificial Intelligence as an enabler of quick and effective production repurposing manufacturing: an exploratory review and future research propositions

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Naz, Farheen, Kumar, Anil, Agrawal, Rohit, Garza-Reyes, Jose Arturo, Majumdar, Abhijit and Chokshi, Hemakshi (2023) Artificial Intelligence as an enabler of quick and effective production repurposing manufacturing: an exploratory review and future research propositions. Production Planning & Control. pp. 1-24. ISSN 0953-7287

Abstract

The outbreak of Covid-19 created disruptions in manufacturing operations. One of the most serious negative impacts is the shortage of critical medical supplies. Manufacturing firms faced pressure from governments to use their manufacturing capacity to repurpose their production for meeting the critical demand for necessary products. For this purpose, recent advancements in technology and artificial intelligence (AI) could act as response solutions to conquer the threats linked with repurposing manufacturing (RM). The study’s purpose is to investigate the significance of AI in RM through a systematic literature review (SLR). This study gathered around 453 articles from the SCOPUS database in the selected research field. Structural Topic Modeling (STM) was utilized to generate emerging research themes from the selected documents on AI in RM. In addition, to study the research trends in the field of AI in RM, a bibliometric analysis was undertaken using the R-package. The findings of the study showed that there is a vast scope for research in this area as the yearly global production of articles in this field is limited. However, it is an evolving field and many research collaborations were identified. The study proposes a comprehensive research framework and propositions for future research development.

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Details
Title:
Artificial Intelligence as an enabler of quick and effective production repurposing manufacturing: an exploratory review and future research propositions
Creators:
Naz, Farheen, Kumar, Anil, Agrawal, Rohit, Garza-Reyes, Jose Arturo, Majumdar, Abhijit and Chokshi, Hemakshi
Identification Number:
https://doi.org/10.1080/09537287.2023.2248947
Official URL:
https://doi.org/10.1080/09537287.2023.2248947
Date:
25 August 2023
Subjects:
000 Computer science, information & general works
600 Technology > 650 Management & auxiliary services
Department:
Guildhall School of Business and Law
Publisher:
Taylor & Francis
Uncontrolled Keywords:
Repurposing manufacturing; Artificial intelligence; Flexible; Structural topic modelling; Adaptable and reconfigurable manufacturing; Text mining; Bibliometric
Additional Information:
Copyright © 2023 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in Production Planning & Control on 25 August 2023, available at: http://www.tandfonline.com/10.1080/09537287.2023.2248947.
Record
URI:
https://repository.londonmet.ac.uk/id/eprint/8673
Item Type:
Article
Depositing User:
Anil Kumar
Date Deposited:
09 Aug 2023 08:23
Revision:
17
Last Modified:
29 Feb 2024 11:27
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