Abstract
Artificial Intelligence (AI) has a growing and wider presence in academic studies and this presence has affected many fields, such as business research, which has picked up on the subject, and AI is now researched from a more holistic perspective, with operations and supply chain management being recognised as one of the areas that is most likely to benefit from AI applications. In addition, many companies have pushed towards using AI in their supply chain processes in order to achieve sustainability. The influence of AI inevitably extends well beyond the production line.
It refers to all business units involved in planning, manufacturing, transporting and selling goods. As a result, companies will need engineering business managers who are well-equipped with know-how of the technological changes that may affect their market and workplace in order to effectively navigate them. This paper proposes a framework that can be used as decision making tools, providing steps for practitioners to consider before and after implementing the AI techniques in their engineering businesses. The framework was developed considering the barriers, enablers and challenges of AI implementation.
It refers to all business units involved in planning, manufacturing, transporting and selling goods. As a result, companies will need engineering business managers who are well-equipped with know-how of the technological changes that may affect their market and workplace in order to effectively navigate them. This paper proposes a framework that can be used as decision making tools, providing steps for practitioners to consider before and after implementing the AI techniques in their engineering businesses. The framework was developed considering the barriers, enablers and challenges of AI implementation.
| Original language | English |
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| Title of host publication | Proceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management, 2021 |
| Place of Publication | Singapore |
| Pages | 5071-5082 |
| Number of pages | 12 |
| Publication status | Published - 7 Mar 2021 |
| Event | 11th Annual International Conference on Industrial Engineering and Operations Management - virtual, Singapore Duration: 7 Mar 2021 → 11 Mar 2021 Conference number: 11 http://ieomsociety.org/singapore2021/ |
Publication series
| Name | Proceedings of the International Conference on Industrial Engineering and Operations Management |
|---|---|
| ISSN (Electronic) | 2169-8767 |
Conference
| Conference | 11th Annual International Conference on Industrial Engineering and Operations Management |
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| Abbreviated title | IEOM |
| Country/Territory | Singapore |
| Period | 7/03/21 → 11/03/21 |
| Internet address |
Bibliographical note
Funding Information:The project described in this paper was under the auspices of the bilateral research collaboration between Coventry University and Institut Teknologi Sepuluh Nopember (ITS), Indonesia. The authors are grateful with the support given by the two institutions.
Publisher Copyright:
© IEOM Society International.
Keywords
- Artificial Intelligence
- Engineering Management
- Operations
- Supply Chain Management
- Sustainability
ASJC Scopus subject areas
- Strategy and Management
- Management Science and Operations Research
- Control and Systems Engineering
- Industrial and Manufacturing Engineering