PLoS ONE · 2021 · 11 citations · 22 references
EngineeringIndustrial EngineeringManufacturing EngineeringQuality AssuranceQuality ControlQuality EngineeringDefect DetectionDefect PreventionQuality Control In ManufacturingBlockchain ConsensusBlockchain SecurityBlockchain-based Data SecurityBlockchain-based SecurityData TransparencyDefect ToleranceMass PersonalizationProduction Quality Assurance
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.
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Data-driven smart manufacturing
Fei Tao, Qinglin Qi, Ang Liu et al. · Journal of Manufacturing Systems · 2018 · 1.7K citations