TY - JOUR
T1 - A sustainable production capability evaluation mechanism based on blockchain, LSTM, analytic hierarchy process for supply chain network
AU - Li, Zhi
AU - Guo, Hanyang
AU - Barenji, Ali Vatankhah
AU - Wang, W. M.
AU - Guan, Yijiang
AU - Huang, George Q.
N1 - Funding Information:
This work was supported by the Natural Science Foundation of Guangdong Province [grant number 2018A0303130035]; and China Postdoctoral Science Foundation [grant number 2018M630928; 2018M633008].
Publisher Copyright:
© 2020 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2020/12/16
Y1 - 2020/12/16
N2 - Due to the rapid development of information technology, supply chain network is evolving, which involves a higher level of interdependence between organisations. Conventional production capability evaluation relies on centralised approaches with limited sharing of performance and evaluation data. Besides, traditional evaluation methods are mainly based on subjective manual operation using limited data. In this paper, we propose a production capability evaluation system by incorporating Internet of Things (IoT), machine learning and blockchain technology for supply chain network. It contributes to achieving real-time data collection and automated enterprise production capability evaluation mechanism. Besides, blockchain technology is adopted to enable open and decentralised data storage and sharing, provide fair and automatic trading of data. The proposed system is evaluated through a simulation experiment. It demonstrated how to utilise the proposed system to choose suitable upstream enterprises. The successful development of the system could help to enhance production efficiency, reduce risk and provide a reasonable and more sustainable production management in supply chain network.
AB - Due to the rapid development of information technology, supply chain network is evolving, which involves a higher level of interdependence between organisations. Conventional production capability evaluation relies on centralised approaches with limited sharing of performance and evaluation data. Besides, traditional evaluation methods are mainly based on subjective manual operation using limited data. In this paper, we propose a production capability evaluation system by incorporating Internet of Things (IoT), machine learning and blockchain technology for supply chain network. It contributes to achieving real-time data collection and automated enterprise production capability evaluation mechanism. Besides, blockchain technology is adopted to enable open and decentralised data storage and sharing, provide fair and automatic trading of data. The proposed system is evaluated through a simulation experiment. It demonstrated how to utilise the proposed system to choose suitable upstream enterprises. The successful development of the system could help to enhance production efficiency, reduce risk and provide a reasonable and more sustainable production management in supply chain network.
KW - blockchain
KW - IoT
KW - machine learning
KW - production capability evaluation
KW - supply chain network
UR - http://www.scopus.com/inward/record.url?scp=85082339201&partnerID=8YFLogxK
U2 - 10.1080/00207543.2020.1740342
DO - 10.1080/00207543.2020.1740342
M3 - Journal article
AN - SCOPUS:85082339201
SN - 0020-7543
VL - 58
SP - 7399
EP - 7419
JO - International Journal of Production Research
JF - International Journal of Production Research
IS - 24
ER -