TY - GEN
T1 - A decision process for the applications of artificial intelligence in sustainable operations and supply chain management
AU - Muhammad, Reza Akbar
AU - Tjahjono, Benny
AU - Kader Ibrahim, Babul Salam K.S.M.
AU - Dewi Ridlo, Sri Rachmi Karimah
AU - Yuwono, Tri Yogi
N1 - Publisher Copyright:
© IEOM Society International.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Artificial Intelligence
KW - Engineering Management
KW - Operations
KW - Supply Chain Management
KW - Sustainability
UR - http://www.scopus.com/inward/record.url?scp=85114253257&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85114253257
SN - 9781792361241
T3 - Proceedings of the International Conference on Industrial Engineering and Operations Management
SP - 5071
EP - 5082
BT - Proceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management, 2021
PB - IEOM Society
T2 - 11th Annual International Conference on Industrial Engineering and Operations Management, IEOM 2021
Y2 - 7 March 2021 through 11 March 2021
ER -