A sustainable production capability evaluation mechanism based on blockchain, LSTM, analytic hierarchy process for supply chain network. Issue 24 (16th December 2020)

• Record Type: Journal Article
• Authors: Li, Zhi; Guo, Hanyang; Barenji, Ali Vatankhah; Wang, W. M.; Guan, Yijiang; Huang, George Q.
• Is Part Of: International journal of production research. Volume 58:Issue 24(2020)
• Page Start: 7399
• Page End: 7419
• Publication Date: 2020-12-16
• Subjects: production capability evaluation -- supply chain network -- blockchain -- IoT -- machine learning; Factory management -- Periodicals; 658.57
• DOI: 10.1080/00207543.2020.1740342
• Languages: English
• ISSNs: 0020-7543

Abstract

Abstract : 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.