Artificial Intelligence for Lean Systems: Systematic Review, Antecedents, Conceptual Mapping, and Future Opportunities
Lean systems thrive on eliminating waste by minimizing all non-value-adding activities. Therefore, significant technological developments such as artificial intelligence (AI) are expected to be swiftly adopted to elevate their performance. While several recent studies have investigated the integrati...
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| Format: | Article |
| Language: | English |
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Ital Publication
2025-04-01
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| Series: | Emerging Science Journal |
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| Online Access: | https://ijournalse.org/index.php/ESJ/article/view/2916 |
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| author | Nasreddine Saadouli Ahmed Elmelegy Raghid Alhajj |
| author_facet | Nasreddine Saadouli Ahmed Elmelegy Raghid Alhajj |
| author_sort | Nasreddine Saadouli |
| collection | DOAJ |
| description | Lean systems thrive on eliminating waste by minimizing all non-value-adding activities. Therefore, significant technological developments such as artificial intelligence (AI) are expected to be swiftly adopted to elevate their performance. While several recent studies have investigated the integration of generic Industry 4.0 tools into lean systems, there is no comprehensive study of the integration of AI in lean systems. Therefore, this study investigates the evolution of the research integrating AI into lean systems from 1993 to 2024 using a thorough bibliometric analysis of 186 peer-reviewed articles retrieved from the Scopus and Web of Science databases. In addition to identifying the body of research’s prevalent intellectual and social structures, thematic clusters and thematic maps are constructed to describe the relevance and development of various research themes. The results reveal no comprehensive and integrative framework with unified terminology and distinct research clusters. Furthermore, the findings indicate a concentration of the research contributions in a small set of developed countries, necessitating the deliberate channeling of funds to enhance this research focus in less developed countries. This work is the first study that explicitly tracks the integration of AI in lean systems and creates a convergent realm of analysis and application by identifying the key research foci and corresponding future trends.
Doi: 10.28991/ESJ-2025-09-02-030
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| format | Article |
| id | doaj-art-3cca1e424c814d0f93e425115edf12b1 |
| institution | OA Journals |
| issn | 2610-9182 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Ital Publication |
| record_format | Article |
| series | Emerging Science Journal |
| spelling | doaj-art-3cca1e424c814d0f93e425115edf12b12025-08-20T01:49:04ZengItal PublicationEmerging Science Journal2610-91822025-04-01921110113210.28991/ESJ-2025-09-02-030827Artificial Intelligence for Lean Systems: Systematic Review, Antecedents, Conceptual Mapping, and Future OpportunitiesNasreddine Saadouli0Ahmed Elmelegy1Raghid Alhajj2Department of Business Administration, Gulf University for Science and Technology, Hawally,Department of Business Administration, Gulf University for Science and Technology, Hawally,Department of Business Administration, Gulf University for Science and Technology, Hawally,Lean systems thrive on eliminating waste by minimizing all non-value-adding activities. Therefore, significant technological developments such as artificial intelligence (AI) are expected to be swiftly adopted to elevate their performance. While several recent studies have investigated the integration of generic Industry 4.0 tools into lean systems, there is no comprehensive study of the integration of AI in lean systems. Therefore, this study investigates the evolution of the research integrating AI into lean systems from 1993 to 2024 using a thorough bibliometric analysis of 186 peer-reviewed articles retrieved from the Scopus and Web of Science databases. In addition to identifying the body of research’s prevalent intellectual and social structures, thematic clusters and thematic maps are constructed to describe the relevance and development of various research themes. The results reveal no comprehensive and integrative framework with unified terminology and distinct research clusters. Furthermore, the findings indicate a concentration of the research contributions in a small set of developed countries, necessitating the deliberate channeling of funds to enhance this research focus in less developed countries. This work is the first study that explicitly tracks the integration of AI in lean systems and creates a convergent realm of analysis and application by identifying the key research foci and corresponding future trends. Doi: 10.28991/ESJ-2025-09-02-030 Full Text: PDFhttps://ijournalse.org/index.php/ESJ/article/view/2916artificial intelligencelean systemsreviewbibliometricknowledge domain. |
| spellingShingle | Nasreddine Saadouli Ahmed Elmelegy Raghid Alhajj Artificial Intelligence for Lean Systems: Systematic Review, Antecedents, Conceptual Mapping, and Future Opportunities Emerging Science Journal artificial intelligence lean systems review bibliometric knowledge domain. |
| title | Artificial Intelligence for Lean Systems: Systematic Review, Antecedents, Conceptual Mapping, and Future Opportunities |
| title_full | Artificial Intelligence for Lean Systems: Systematic Review, Antecedents, Conceptual Mapping, and Future Opportunities |
| title_fullStr | Artificial Intelligence for Lean Systems: Systematic Review, Antecedents, Conceptual Mapping, and Future Opportunities |
| title_full_unstemmed | Artificial Intelligence for Lean Systems: Systematic Review, Antecedents, Conceptual Mapping, and Future Opportunities |
| title_short | Artificial Intelligence for Lean Systems: Systematic Review, Antecedents, Conceptual Mapping, and Future Opportunities |
| title_sort | artificial intelligence for lean systems systematic review antecedents conceptual mapping and future opportunities |
| topic | artificial intelligence lean systems review bibliometric knowledge domain. |
| url | https://ijournalse.org/index.php/ESJ/article/view/2916 |
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