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

Zhi Li, Hanyang Guo, Ali Vatankhah Barenji, W. M. Wang, Yijiang Guan, George Q. Huang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

87 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)7399-7419
Number of pages21
JournalInternational Journal of Production Research
Volume58
Issue number24
DOIs
Publication statusPublished - 16 Dec 2020
Externally publishedYes

Keywords

  • blockchain
  • IoT
  • machine learning
  • production capability evaluation
  • supply chain network

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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