A Consortium Blockchain and Smart Contract Framework for End-to-End Traceability and Counterfeit Prevention in Automotive Manufacturing

Abstract

The paper suggests a blockchain-based framework to guarantee the automotive parts traceability and anti-counterfeiting with the help of a consortium blockchain solution. The goal will be to handle the issues of fraud and the transparency gap in the automotive supply chain through the utilization of Hyperledger Fabric and smart contracts. The framework incorporates smart contracts to automate the traceability and implement anti-counterfeiting. A network of Hyperledger Fabric v2.5 was created, which modeled the supply chain of 10,000 automotive parts (brake calipers) in a realistic way. The Auto Parts Dataset of Kaggle was employed to test the framework, where fake counterfeit parts had been simulated. Measures of performance such as transaction throughput (TPS), latency, and the ability to detect fraud were analyzed. The accuracy of the framework in detecting counterfeit was 98.1%, and the undetected fraud rate was decreased to less than 0.2 compared to 35-40% before. The blockchain system completed 1,820 transactions in one second, and the 95th percentile latency is 1.8 seconds, which corresponds to industry standards. The findings can illustrate how the framework can be used to improve transparency in the supply chain, avoid fake components, and streamline real-time verification. The solution proposed will provide a scalable solution in preventing counterfeit parts within the automotive supply chain to enhance traceability and minimize the losses involved in fraud. More studies are required to improve the scalability and integration of the framework to the IoT devices and to investigate other consensus blockchain algorithms.