The improvement of the inherent reliability of mechanical components has a significant impact on enterprise reputation and performance. To estimate product inherent reliability more conveniently and economically, a reliability prediction model based on Hidden Quality Loss (HQL) is proposed. To obtain a more accurate estimation of Hidden Quality Cost (HQC), an asymmetric quadratic exponential Quality Gain-Loss Function (QGLF) model is established. Unlike Taguchi’s quadratic quality loss function (QLF) and its modified versions, the new QLF model not only considers the different growth rates of quality loss on both sides of the target value but also accounts for the compensation effects among different processes. Under the assumption that quality characteristics follow a normal distribution, and sampling errors are considered, a general estimation formula for HQC within the tolerance range is derived, and a numerical model of inherent reliability is established. Based on this model, the relationship between product reliability and the Process Capability Index (PCI) is deduced. The effects of different manufacturing conditions and process parameters on inherent product reliability are discussed. Finally, appropriate PCIs are selected according to different production processes, and a case study on friction plates is presented for verification.
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