Applied Artificial Intelligence in Manufacturing and Industrial Production Systems: PEST Considerations for Engineering Managers
Akinsolu, Mobayode O. (2022) Applied Artificial Intelligence in Manufacturing and Industrial Production Systems: PEST Considerations for Engineering Managers. IEEE Engineering Management Review, 51 (1). pp. 52-62. ISSN 1937-4178
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Abstract
Presently, artificial intelligence (AI) is playing a leading role in our contemporary world via numerous applications. Despite its many advantages, analytical frameworks highlighting the implications of AI applications are still evolving. Particularly, in manufacturing and industrial production where novel technologies are continuously being harnessed. Consequently, AI and the implications of its applications have relatively remained a gray area for many engineering managers who are key players in the gravitation of manufacturing and industrial production toward the fourth industrial revolution and more recently, the fifth industrial revolution, generally termed as Industry 4.0 (I4.0) and Industry 5.0 (I5.0), respectively. In this study, the implications of AI applications in the general context of manufacturing and industrial production, are presented to provide insight for engineering managers. These implications are discussed via political, economic, social, and technological (PEST) considerations of the broad impact of the adoption of AI techniques in manufacturing and industrial production systems. A new engineering management model has not been proposed in this article. Rather, a discussion aimed at serving as a tool for the appraisal of the implications of the general applications of AI by engineering managers, who may not be AI specialists or data science experts is presented.
| Item Type: | Article |
|---|---|
| Keywords: | Artificial intelligence (AI), engineering management, industrial production, manufacturing, political, economic, social, and technological (PEST) analysis, Industry 4.0, Industry 5.0 |
| Divisions: | Applied Science, Computing and Engineering |
| Depositing User: | Hayley Dennis |
| Date Deposited: | 03 Jul 2023 12:46 |
| Last Modified: | 03 Jul 2023 12:46 |
| URI: | https://glyndwr.repository.guildhe.ac.uk/id/eprint/18031 |
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