Artificial Intelligence as an enabler of quick and effective production repurposing manufacturing: an exploratory review and future research propositions
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 criti...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English English |
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Taylor & Francis
2023
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| Online Access: | https://repository.londonmet.ac.uk/8673/3/Accepted%20Version%20-1.pdf https://repository.londonmet.ac.uk/8673/9/Artificial%20intelligence%20as%20an%20enabler%20of%20quick%20and%20effective%20production%20repurposing%20%20an%20exploratory%20review%20and%20future%20research%20propositions.pdf |
| _version_ | 1804072931601416192 |
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| author | Naz, Farheen Kumar, Anil Agrawal, Rohit Garza-Reyes, Jose Arturo Majumdar, Abhijit Chokshi, Hemakshi |
| author_facet | Naz, Farheen Kumar, Anil Agrawal, Rohit Garza-Reyes, Jose Arturo Majumdar, Abhijit Chokshi, Hemakshi |
| author_sort | Naz, Farheen |
| collection | LMU |
| description | 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. |
| first_indexed | 2024-07-09T04:06:59Z |
| format | Article |
| id | oai:repository.londonmet.ac.uk:8673 |
| institution | London Metropolitan University |
| language | English English |
| last_indexed | 2024-07-09T04:06:59Z |
| publishDate | 2023 |
| publisher | Taylor & Francis |
| record_format | eprints |
| spelling | oai:repository.londonmet.ac.uk:86732024-02-29T11:27:55Z http://repository.londonmet.ac.uk/8673/ Artificial Intelligence as an enabler of quick and effective production repurposing manufacturing: an exploratory review and future research propositions Naz, Farheen Kumar, Anil Agrawal, Rohit Garza-Reyes, Jose Arturo Majumdar, Abhijit Chokshi, Hemakshi 000 Computer science, information & general works 650 Management & auxiliary services 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. Taylor & Francis 2023-08-25 Article PeerReviewed text en cc_by_nc_nd_4 https://repository.londonmet.ac.uk/8673/3/Accepted%20Version%20-1.pdf text en cc_by_nc_nd_4 https://repository.londonmet.ac.uk/8673/9/Artificial%20intelligence%20as%20an%20enabler%20of%20quick%20and%20effective%20production%20repurposing%20%20an%20exploratory%20review%20and%20future%20research%20propositions.pdf 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 https://doi.org/10.1080/09537287.2023.2248947 10.1080/09537287.2023.2248947 |
| spellingShingle | 000 Computer science, information & general works 650 Management & auxiliary services Naz, Farheen Kumar, Anil Agrawal, Rohit Garza-Reyes, Jose Arturo Majumdar, Abhijit Chokshi, Hemakshi Artificial Intelligence as an enabler of quick and effective production repurposing manufacturing: an exploratory review and future research propositions |
| title | Artificial Intelligence as an enabler of quick and effective production repurposing manufacturing: an exploratory review and future research propositions |
| title_full | Artificial Intelligence as an enabler of quick and effective production repurposing manufacturing: an exploratory review and future research propositions |
| title_fullStr | Artificial Intelligence as an enabler of quick and effective production repurposing manufacturing: an exploratory review and future research propositions |
| title_full_unstemmed | Artificial Intelligence as an enabler of quick and effective production repurposing manufacturing: an exploratory review and future research propositions |
| title_short | Artificial Intelligence as an enabler of quick and effective production repurposing manufacturing: an exploratory review and future research propositions |
| title_sort | artificial intelligence as an enabler of quick and effective production repurposing manufacturing an exploratory review and future research propositions |
| topic | 000 Computer science, information & general works 650 Management & auxiliary services |
| url | https://repository.londonmet.ac.uk/8673/3/Accepted%20Version%20-1.pdf https://repository.londonmet.ac.uk/8673/9/Artificial%20intelligence%20as%20an%20enabler%20of%20quick%20and%20effective%20production%20repurposing%20%20an%20exploratory%20review%20and%20future%20research%20propositions.pdf |
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