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On the generalized process capability under simple and mixture models

机译：简单模型和混合模型下的广义过程能力

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摘要

Process capability (PC) indices measure the ability of a process of interest to meet the desired specifications under certain restrictions. There are a variety of capability indices available in literature for different interest variables such as weights, lengths, thickness, and the life time of items among many others. The goal of this article is to study the generalized capability indices from the Bayesian view point under different symmetric and asymmetric loss functions for the simple and mixture of generalized lifetime models. For our study purposes, we have covered a simple and two component mixture of Maxwell distribution as a special case of the generalized class of models. A comparative discussion of the PC with the mixture models under Laplace and inverse Rayleigh are also included. Bayesian point estimation of maintenance performance of the system is also part of the study (considering the Maxwell failure lifetime model and the repair time model). A real-life example is also included to illustrate the procedural details of the proposed method.
机译：流程能力（PC）指数用于衡量目标流程在某些限制下满足所需规格的能力。文献中有许多针对不同兴趣变量的能力指标，例如重量，长度，厚度和物品的使用寿命等。本文的目的是从贝叶斯的角度研究简单寿命和混合寿命模型在不同对称和非对称损失函数下的广义能力指标。为了我们的研究目的，我们讨论了麦克斯韦分布的简单和两部分混合，作为广义模型类别的特例。还包括PC与Laplace和逆瑞利混合模型下的比较讨论。系统维护性能的贝叶斯点估计也是研究的一部分（考虑麦克斯韦故障寿命模型和维修时间模型）。还包括一个真实的例子来说明所提出方法的程序细节。

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