Blockchain-based credible manufacturing data sharing for a collaborative manufacturing supply chain

ABSTRACTCore enterprises are entering into close collaborations with multi-level manufacturing service providers to create and share value. However, credible data sharing in collaborative manufacturing supply chains is rare, which can lead to uncontrollable production distortions and delayed operational adjustments. Driven by blockchain technology, this study proposes a systematic framework for credible manufacturing data sharing for a cross-enterprise collaborative manufacturing supply chain (CMSC). To develop the needed method, a blockchain network system with blockchain nodes, distributed ledger, and Raft-based distributed node ordering service system was first modelled. Then, two automatic data upload algorithms were studied to ensure the reliability of off-chain manufacturing data sources from core enterprises, suppliers, and customers. Then, two types of smart contracts were designed to ensure the standardisation and co-validation of manufacturing data storage and query processes in the blockchain network. A demonstrative case was studied to validate the proposed blockchain-based credible manufacturing data sharing method. The results show that our work is effective for credible data sharing in CMSC, which makes it easier for core enterprises to better operate the CMSC and further stimulate enterprises to create a credible social community.KEYWORDS: Blockchain networkcollaborative manufacturing supply chaindata sharingcredibilitysmart contract Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe authors acknowledge that the data supporting the findings of this study are available in the article and its supplemental materials.Additional informationFundingThis work was supported by the National Key Research and Development Program of China under grant number 2021YFB3301702, China Postdoctoral Science Foundation under grant numbers 2021M700528 and 2022T150073, Macau University of Science and Technology Faculty Research Grants (FRG) under grant number FRG-22-108-MSB, National Natural Science Foundation of China (NSFC) under grant number 71971143, and The Macau Foundation Fund (MFP) under grant number MF-23-008-R.Notes on contributorsKangqian ZhengKangqian Zheng received B.S. degree in Mechanical and Electronic Engineering from Shaanxi University of Science and Technology, China, in 2020. He is currently pursuing his Ph.D. degree in Mechanical Engineering in Chang’an University, China. His research interests include blockchain-based collaborative manufacturing.Kai DingKai Ding received the B.S. degree and Ph.D. degree in Mechanical Engineering from China University of Mining and Technology, China and Xi’an Jiaotong University, China, in 2011 and 2017, respectively. He is currently an Associate Professor with the Institute of Smart Manufacturing Systems, Chang’an University. His research interests mostly lie in the smart manufacturing system fields, by leveraging the cutting-edge information technology and artificial intelligence to solve the sophisticated production control issues.Jizhuang HuiJizhuang Hui received the B.S. degree in Mechanical and Electronic Engineering from Dalian University of Technology, China, in 1995. He received the M.S. degree and Ph.D. degree from Chang’an University, China, in 2001 and 2010, respectively. He is currently a professor with the Institute of Smart Manufacturing Systems, Chang’an University, China. His research interests include IIoT and smart manufacturing systems engineering.Fuqiang ZhangFuqiang Zhang received the B.S. degree in Mechanical Engineering from Zhengzhou University, China, in 2006. He received the Ph.D. degree in Mechanical Engineering in Xi’an Jiaotong University, China, in 2013. He is currently an Associate Professor with the Institute of Smart Manufacturing Systems, Chang’an University, China. His current research focuses on service-oriented manufacturing and production-logistics operations management.Jingxiang LvJingxiang Lv received the B.Eng. degree in industrial engineering and the Ph.D. degree in mechanical engineering from Zhejiang University, China, in 2008 and 2014, respectively. He is currently an Associate Professor with the Institute of Smart Manufacturing Systems, Chang’an University, China. His research interests include big data, green manufacturing, energy consumption modelling, and optimisation.Felix T.S. ChanFelix T. S. Chan received his B.S. Degree in Mechanical from Brighton University, UK, in 1981, and obtained his M.S. and Ph.D. in the Imperial College of Science and Technology, University of London, UK, in 1982 and 1986, respectively. He is now working at the Department of Decision Sciences, Macau University of Science and Technology, Macao SAR, China. His current research interests are logistics and supply chain management, production operations management, distribution coordination, systems modelling and simulation.