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Reliability analysis for mechanical parts considering hidden cost via the modified quality loss model
Author(s) -
Mao Kui,
Liu Xintian,
Li Shuangshuang,
Wang Xu
Publication year - 2021
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2800
Subject(s) - reliability (semiconductor) , reliability engineering , quality (philosophy) , taguchi methods , production (economics) , range (aeronautics) , function (biology) , process (computing) , exponential function , computer science , mathematical optimization , engineering , mathematics , mathematical analysis , power (physics) , philosophy , physics , epistemology , quantum mechanics , evolutionary biology , biology , economics , macroeconomics , aerospace engineering , operating system , machine learning
The improvement of mechanical parts inherent reliability has an impact on the reputation and performance of the company. To estimate the inherent reliability of products more conveniently and economically, a hidden quality cost‐production cost (HQC‐PC) reliability prediction model is put forward. To estimate the hidden quality cost (HQC) of products more accurately, a quadratic exponential quality loss function model is established, which is different from Taguchi's quadratic quality loss function (QLF) and the modified QLFs. In the new quality loss model, the growth rate of quality loss on both sides of the target value is considered. Under the condition that the quality characteristic value obeys normal distribution, the general estimation formulas of HQC in the tolerance range is obtained considering sampling error and the numerical model of inherent reliability is established. The effect of different parameters on the inherent reliability of products is discussed with practical case, such as design and production parameters. Then, the appropriate process capability index (PCI) is selected according to different production processes. The relationship between the HQC‐PC reliability prediction model and PCI is derived by a numerical model of inherent reliability. A new analysis method of inherent reliability is proposed.