Remanufacturing workshop management in blockchain and digital twin-based cloud remanufacturing service platform

Q Qin Xiang (Marshall Laboratory of Biomedical Engineering, Precision Medicine and Health Research Institute, Shenzhen Key Laboratory for Nano-Biosensing Technology, Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School) X Xugang Zhang Y Yan Wang

Abstract

The cloud remanufacturing service platform is an online platform that provides various services and resources for the remanufacturing industry. It promotes the digital transformation of the industry, improves resource utilization efficiency, and reduces environmental impact. However, there are prominent issues in sharing remanufacturing data securely, monitoring the remanufacturing process opaquely, and dealing with high uncertainties in remanufacturing operations within the remanufacturing intelligent workshop, which is an important component of the platform. This paper combines blockchain technology and digital twin technology to study the management mode of the remanufacturing workshop under the cloud remanufacturing service platform. Firstly, the overall framework of the cloud remanufacturing service platform is constructed, and a dual-chain structure with expandable subchains for storing transaction data and workshop data is designed. Secondly, by connecting the remanufacturing workshop with smart contracts and digital twin, real-time monitoring, remote collaboration, and data analysis optimization of the remanufacturing workshop are achieved. Digital twin is applied to the remanufacturing process, and a digital twin-based remanufacturing workshop architecture is established. The key technologies involved are analyzed. Finally, the management mode of the automotive remanufacturing workshop under the cloud-based remanufacturing service platform based on blockchain and digital twin is explored.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 21, Issue 3
Published March 27, 2026
Pages e0345757
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (3)

Q

Qin Xiang

Marshall Laboratory of Biomedical Engineering, Precision Medicine and Health Research Institute, Shenzhen Key Laboratory for Nano-Biosensing Technology, Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School

X

Xugang Zhang

Y

Yan Wang