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Blockchain in manufacturing quality control: A computer simulation study

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  • Pooi-Mun Wong
  • Shreya R. K. Sinha
  • Chee-Kong Chui

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.

Suggested Citation

  • Pooi-Mun Wong & Shreya R. K. Sinha & Chee-Kong Chui, 2021. "Blockchain in manufacturing quality control: A computer simulation study," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-23, March.
    • Handle: RePEc:plo:pone00:0247925
    DOI: 10.1371/journal.pone.0247925
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    References listed on IDEAS

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    1. Taehyun Ko & Jaeram Lee & Doojin Ryu, 2018. "Blockchain Technology and Manufacturing Industry: Real-Time Transparency and Cost Savings," Sustainability, MDPI, vol. 10(11), pages 1-20, November.
    2. Ahmad Firdaus & Mohd Faizal Ab Razak & Ali Feizollah & Ibrahim Abaker Targio Hashem & Mohamad Hazim & Nor Badrul Anuar, 2019. "The rise of “blockchain”: bibliometric analysis of blockchain study," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 1289-1331, September.
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