Blockchain in manufacturing quality control: A computer simulation study

Abstract

Blockchain has been applied to quality control in manufacturing, but the problems of false defect detections and lack of data transparency remain. This paper proposes a framework, Blockchain Quality Controller (BCQC), to overcome these limitations while fortifying data security. BCQC utilizes blockchain and Internet-of-Things to form a peer-to-peer supervision network. This paper also proposes a consensus algorithm, Quality Defect Tolerance (QDT), to adopt blockchain for during-production quality control. Simulation results show that BCQC enhances data security and improves defect detections. Although the time taken for the quality control process increases with the number of nodes in blockchain, the application of QDT allows multiple inspections on a workpiece to be consolidated at a faster pace, effectively speeding up the entire quality control process. The BCQC and QDT can improve the quality of parts produced for mass personalization manufacturing.

Integrating Lean Six Sigma with blockchain technology for quality management – a scoping review of current trends and future prospects

“…The false defect detection in workpieces during the production stage and limited data transparency motivate blockchain technology to improve the quality control process (Ko et al, 2018). Based on Wong et al (2021), the blockchain quality controller (BCQC) helps to strengthen the data security issues of existing solutions. This controller also helps to propose a consensus contract called Quality defect tolerance (QDT) that assists in adopting the blockchain during the workpiece production phase and selects an inspection result from a pool of inspection results based on the consensus by multiple members.…”

“…The trusted fish provenance data is protected by the blockchain that can assist in assessing the quality of fish throughout the supply chain stages (Hang et al, 2020). In this context, Wong et al (2021) have proposed a blockchain-enabled highly secure fish provenance and quality tracking (BeFAQT) system that automatically and accurately assesses the quality of fish by recording and verifying the fish temperature and location data. The BeFAQT system has implemented Attribute-Based Encryption (ABE) schemes to securely exchange data among the participants, thus solving the data privacy issue of blockchain technology.…”

“…The industries such as Manufacturing quality control (MQC), and Healthcare quality control (HQC) have been chosen by the majority of the studies for assuring quality control in supply chain processes. The studies (Wong et al, 2021;Arena et al, 2019;Yuan et al, 2018;Feng et al, 2020;Casino et al, 2021;Voulgaris et al, 2020;Assaqty et al, 2020;Wong et al, 2021;Park et al, 2020;Zhong et al, 2020;Shahbazi and Byun, 2021) have considered the manufacturing industry for quality control and safety of olive oil, fish, construction material and other items using blockchain and IoT technologies. Likewise, studies such as those (Qiu and Zhu, 2021;Tseng et al, 2018;Liu et al, 2021;Uddin, 2021;Yik et al, 2021) have taken the healthcare sector as an example to ensure the quality of administered drugs and types of consigned equipment.…”

“…Many of the studies presented in Table 1 have employed IoT-based asset monitoring to ensure the safety of the asset during the manufacturing, distribution, storage, and processing stages. Few of the existing studies have implemented AI and machine learning techniques to ensure the quality of shipping items using different models that are trained based on trusted and highly reliable blockchain-based data (Wong et al, 2021;Feng et al, 2020;Park et al, 2020;Shahbazi and Byun, 2021). For instance, through AI-based models, the freshness level of shipped manufactured items can be verified.…”

“…The permissionless platforms are slow and less secure as they can be accessed publicly. Existing quality control-related studies such as (Wong et al, 2021;Casino et al, 2021;Qiu and Zhu, 2021) have employed the Ethereum blockchain platform to develop blockchain-based applications to monitor the quality of assets. On the other hand, studies such as (Arena et al, 2019;Assaqty et al, 2020;Park et al, 2020;Zhong et al, 2020;Shahbazi and Byun, 2021) have considered the Hyperledger Fabric platform to develop DApp applications to verify and control the quality of assets.…”