A sustainable production capability evaluation mechanism based on blockchain, LSTM, analytic hierarchy process for supply chain network

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. Be...

Full description

Saved in:
Bibliographic Details
Published in:International journal of production research 2020-12, Vol.58 (24), p.7399-7419
Main Authors: Li, Zhi, Guo, Hanyang, Barenji, Ali Vatankhah, Wang, W. M., Guan, Yijiang, Huang, George Q.
Format: Article
Language:English
Subjects:
Analytic hierarchy process
Automation
Blockchain
Cryptography
Data collection
Data storage
Internet of Things
IoT
Machine learning
Performance evaluation
production capability evaluation
Production management
Risk management
supply chain network
Supply chains
Sustainable development
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2020.1740342