A Decision Process for the Applications of Artificial Intelligence in Sustainable Operations and Supply Chain Management

Reza Akbar Muhammad, Benny Tjahjono, Babul KSM Kader Ibrahim, Sri Rachmi Karimah Dewi Ridlo, Tri Yogi Yuwono

Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

1 Citation (Scopus)

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.
Original languageEnglish
Title of host publicationProceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management, 2021
Place of PublicationSingapore
Pages5071-5082
Number of pages12
Publication statusPublished - 7 Mar 2021
Event11th Annual International Conference on Industrial Engineering and Operations Management
- virtual, Singapore
Duration: 7 Mar 202111 Mar 2021
Conference number: 11
http://ieomsociety.org/singapore2021/

Publication series

NameProceedings of the International Conference on Industrial Engineering and Operations Management
ISSN (Electronic)2169-8767

Conference

Conference11th Annual International Conference on Industrial Engineering and Operations Management
Abbreviated titleIEOM
Country/TerritorySingapore
Period7/03/2111/03/21
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

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