Blockchain-based Quality Traceability Management of Ready-mixed Concrete Supply Chain

Abstract

Ready-mixed concrete (RMC) is a critical construction material whose quality directly impacts the safety, durability, and performance of construction projects. However, the existing quality management of ready mixed concrete is discontinuous and untimely, and relies on periodic self-inspection and sampling inspection in stages, which leads to the lack of real-time monitoring and dynamic disposal ability of quality data, and makes RMC quality problems occur from time to time. Besides, data interactions among various stages and stakeholders depend on paper documents and centralized databases, leading to difficulties in sharing quality information and the establishment of an effective quality traceability mechanism. The objective of this research is to apply blockchain technology to establish the theoretical model and technical methods for quality traceability management in the RMC concrete supply chain, thereby enhancing the standardization and intelligence of the entire quality management process of RMC.

This research is grounded in the theory of supply chain management and information flow management to develop a blockchain-based quality traceability management model for the RMC supply chain, focusing on the triadic trustworthiness of identity, data, and behavior. Further, quality data traceability management methods are proposed based on the principles of reliability, traceability, shareability, and verifiability. Finally, a blockchain-based quality traceability platform for the RMC supply chain is developed, and a case study is conducted for practical validation in a cast-in-place concrete section of a transportation infrastructure construction project. The contributions of this research are as follows.

(1) Existing research primarily focuses on the traceability management of quality data, lacking exploration of comprehensive quality traceability mechanisms within complex supply chains. Hence, this research utilizes the Design Science Research (DSR) paradigm to propose a blockchain-based quality traceability management model for the RMC supply chain. The quality traceability management mechanisms of the model are designed from three aspects: identity trustworthiness (ensuring reliable stakeholder identities and privacy protection), data trustworthiness (ensuring the authenticity and immutability of information), and behavior trustworthiness (ensuring the traceability and verifiability of actions). The model addresses the shortcomings of traditional quality traceability systems, significantly enhancing the transparency and accountability of quality management processes, and lays the foundation for subsequent quality traceability method design.

(2) Considering the real-time and high-frequency interaction demands of the RMC supply chain, a hybrid transmission method for large-scale, multi-source heterogeneous quality data based on blockchain, ensuring efficient storage and sharing of quality information as well as data traceability and reliability. Specifically, a dual-layer data storage method based on blockchain and the InterPlanetary File System (IPFS) is proposed to resolve issues related to storage efficiency and data format compatibility inherent in traditional blockchain systems by storing textual data and large files in hierarchical layers. Furthermore, a Feature and Credit-based Byzantine Fault Tolerance (FCBFT) consensus algorithm is proposed, enhancing consensus efficiency in high-concurrency environments through feature grouping, credit-based incentive mechanism, and optimized consensus node selection strategy. Finally, simulation experiments are conducted to validate the feasibility and reliability of these methods, significantly improving the efficiency and reliability of information exchange within large-scale consortium blockchains.

(3) To address the time-consuming and labor-intensive nature of quality inspection for RMC and the delayed response to quality issues, this research proposes a smart contract and knowledge graph-based quality information inspection and issue traceability method. This method can provide a structured approach to storing RMC quality knowledge and enables quality data inspection and dynamic problem response at the semantic rule level. Specifically, a smart contract-based quality information inspection method is proposed, allowing automatic inspection of the uploaded RMC quality parameters, thereby enhancing the transparency, standardization, and efficiency of the quality acceptance work. Moreover, an intelligent smart contract generation algorithm is designed, utilizing knowledge graphs and recursive descent semantic analysis to establish a syntax parser for smart contracts. It effectively facilitates the automatic conversion from semantic rules to machine-readable contracts and allows construction professionals to quickly generate smart contracts that meet the RMC supply chain quality management needs.

This research initially realizes the innovative application of blockchain technology in the quality traceability management of the RMC supply chain, which enriches the knowledge of blockchain application in construction logistics, and promotes the quality management of RMC.

Date of Award	9 Sept 2025
Original language	English
Awarding Institution	City University of Hong Kong
Supervisor	Hao Hu (External Supervisor) & Xiaowei LUO (Supervisor)