Classification method and classification device for product quality risks

Abstract

The invention discloses a product quality risk classification method and classification device. The classification method comprises the following steps: establishing a risk factor analysis matrix; processing the risk factor analysis matrix based on a preset projection algorithm to obtain a processed matrix; performing risk analysis on the processed matrix based on a preset analysis method to obtain a risk analysis result; and performing classification processing on the risk analysis result based on a preset classification algorithm to obtain a corresponding risk classification result. By comprehensively considering the weight of each engineer and based on a grey correlation analysis method and a self-adaptive resonance theory, the method effectively eliminates the inconsistency of different persons during risk assessment, and meanwhile, the risk categories are accurately and effectively distinguished, and the risk classification accuracy is improved.

Description

technical field [0001] The invention relates to the technical field of risk management, in particular to a product quality risk classification method and a product quality risk classification device. Background technique [0002] In a series of production processes such as product design, production, and assembly, it is necessary to carry out quality risk management activities to assess, control and review possible quality risks throughout the product life cycle. [0003] As a risk assessment and prevention tool, Failure Mode and Effects Analysis (FMEA) is widely used in product design and production. In traditional FMEA, risk priority number (Risk Priority Number, RPN), an important indicator for assessing risk priority, is calculated from three influencing factors: severity (S), frequency (O) and detection degree (D). [0004] Although FMEA is widely used in the field of quality risk assessment, in the actual application process, technicians have found that the existing F...

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Problems solved by technology

[0005] (1) Due to the subjectivity and inconsistency in the scores of the engineering personnel of the FMEA team during the above calculation process, it will lead to inaccuracies in the risk assessment process and results;

[0006] (2) Due to the discreteness of the values ​​of S, O, and D risk factors and the irrationality of the RPN algorithm, it will further lead to uncertainty and inaccuracy in the risk assessment process and results;

[0007] (3) In the traditional FMEA model, in the process of quality risk assessment, the simultaneous consideration of risk factors will lead to the weakening of the impact of extreme risk factors by general risk factors, resulting in the lack of risk information and the inability to accurately identify extreme risk factors during the assessment process. Effect of Risk Factors on Failure Modes

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