Process machining allowance for reliability analysis of mechanical parts based on hidden quality loss

• Autorzy: Wang Jingang , Liu Xintian , Wang Xu , Jin Kai

Identyfikatory

DOI

10.17531/ein/171594

• Języki publikacji: EN

Abstrakty

EN

The machining allowance variation is significant for the reliability of a part during the machining process. Usually, when the machining allowance of a part increases, the machining and production cost also increase. When the machining allowance decreases, the machining surface will have defects. The parts will produce manyscraps andreliability will decrease. The machining allowance of a part consists of multiple process machining allowances. To analyze the impact caused by machining allowance variation, the hidden quality loss and process machining allowance are combined through theprocess capability index (PCI). Then the asymmetric quadratic quality loss function (AQF) and quadratic exponential function (QEF) are used to analyze them. A prediction model of hidden quality loss of process machining allowance is proposed. On the premise that the quality characteristic value obeys normal function distribution, a numerical model is given and used to obtain process machining allowance-inherent reliability of the product. The actual case is used to compare and verify the two models.

Słowa kluczowe

EN

reliability analysis; process machining allowance; hidden quality loss; process capability index

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2023
• Tom: Vol. 25, no. 4
• Strony: art. no. 171594
• Opis fizyczny: Bibliogr. 38 poz., fot., rys., tab., wykr.

Twórcy

autor

Wang Jingang

• School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, China

autor

Liu Xintian

• School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, China

• https://orcid.org/0000-0002-3395-9176

autor

Wang Xu

• School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, China

autor

Jin Kai

• School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, China

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