4.3 Article

Root cause identification approach using decomposition of QFD and extended RPN for product manufacturing reliability degradation

Publisher

SAGE PUBLICATIONS LTD
DOI: 10.1177/1748006X211043656

Keywords

Product manufacturing reliability; reliability degradation; root cause identification; quality function deployment; extended risk priority number

Funding

  1. National Natural Science Foundation of China [72071007, 71971181]

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Reliability is crucial in product manufacturing, and root cause analysis can help identify vulnerable parameters that may degrade product reliability. This study proposes a root cause identification approach based on QFD and RPN to prevent the degradation of product manufacturing reliability.
Reliability is reflected in product during manufacturing. However, due to uncontrollable factors during production, product reliability may degrade substantially after manufacturing. Thus, root cause analysis is important in identifying vulnerable parameters to prevent the product reliability degradation in manufacturing. Therefore, a novel root cause identification approach based on quality function deployment (QFD) and extended risk priority number (RPN) is proposed to prevent the degradation of product manufacturing reliability. First, the connotation of product manufacturing reliability and its degradation mechanism are expounded. Second, the associated tree of the root cause of product manufacturing reliability degradation is established using the waterfall decomposition of QFD. Third, the classic RPN is extended to focus on importance to reliability characteristics, probability, and un-detectability. Furthermore, fuzzy linguistic is adopted and the integrated RPN is calculated to determine the risk of root causes. Therefore, a risk-oriented root cause identification technique of product manufacturing reliability degradation is proposed using RPN. Finally, a root cause identification of an engine component is presented to verify the effectiveness of this method. Results show that the proposed approach can identify the root cause objectively and provide reference for reliability control during production.

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