质量控制中完全检验的一种最优设计

本文提出质量控制中完全检验的一种最优设计。所谓完全检验 ,也就是 1 0 0 %检验 ,是指生产出来的每一个产品都要经过检验。生产过程中有两种生产状态 :控制状态和失控状态。当一个产品的质量特征值超过预定的控制界限 ,就立即对生产过程进行检查 ,一旦发现生产失控 ,马上采取调整措施使生产恢复正常。检验后的产品按其质量特征值接受或者重新制作。根据本文所建立的质量成本模型 ,我们可以得到最优的产品质量的规格界限和控制界限 ,对实际企业的生产有积极的指导作用。     

AT&T准则下完全检验的最优设计

本文研究了完全检验的质量控制问题,将广泛用于X-控制图的AT&T准则应用于完全检验,并根据完全检验的特点,提出一种新的最优模型,数值实验结果表明AT&T准则下的完全检验优于传统的完全检验.     

AT&T准则下完全检验的最优设计(英文)

本文研究了完全检验的质量控制问题,将广泛用于X-控制图的AT＆amp;T准则应用于完全检验,并根据完全检验的特点,提出一种新的最优模型,数值实验结果表明AT＆amp;T准则下的完全检验优于传统的完全检验。     

完全区组设计下基于Aligned秩的有方向检验问题

本文基于Aligned秩给出了用于解完全区组设计有方向检验问题的, 我们称之为$C$-检验的检验方法. 本文分别对每个试验单元仅有一个观测值以及等重复观测值和不等重复观测值各种情形下的$C$检验进行了讨论, 并在原假设$H_0$成立时计算了上述各种情形下$C$检验统计量的数学期望和方差, 且证明了$C$检验统计量的渐近分布为正态分布.     

两变量随机截距模型的最优设计

本文考虑两变量随机截距模型在单位正方形设计域上的D-,G-,A-,Ds-和I-最优设计.证明了最优设计在设计区域的顶点处获得,得到了几类不依赖于随机截距项的最优设计模拟结果表明最优设计较随机设计可大幅提高参数估计的精确性.     

一种估计精度限制下的加速退化试验最优设计

讨论了一类步进应力的加速退化试验,在试验假定下,以退化失效分布平均寿命的极大似然估计与其真值的接近程度为标准得到一个精度限制．然后根据试验的过程得到了试验成本函数的一般表达形式．在估计精度的限制之下,最小化成本函数,以此得出试验的最优设计模型．最后,给出了一个数值例子,展示了优化设计的过程．     

两变量随机系数回归模型的最优设计

本文考虑两变量随机系数回归模型在单位正方形设计区域上基于A-,Ds-,I-和D-准则下的最优设计.证明了最优设计可在设计域的顶点处获得,并得到了几类最优设计的解析或数值结果.     

制造商检验的最优质量水平及影响因素研究

为提高我国食品质量安全水平,对小型、分散的单个供应商和一个制造商构成的食品供应链中,制造商对原材料和最终食品进行质量检测的情况,建立了以供应商和制造商各自的质量水平为决策变量的优化模型,分析了最优质量水平的影响因素和影响效应.并依据结论提出相应建议,如提高消费者对优劣食品的识别能力,发挥制造商在供应链中的监督检验作用等.     

用两个V函数判别非自治系统的完全渐近稳定性

本文用两个Ｖ函数对一般非自治系统建立了完全渐进稳定性的一类判别条件．     

Economic optimization of off-line inspection with rework consideration

This paper addresses issues relating to off-line inspection with rework consideration. We develop a mathematical model to determine the first unit inspected and the average number to be inspected in a batch, assuming the involvement of a quality-control department with a standard procedure. Numerical analyses are used to simulate the effect of changes in the various parameters on the optimal solution when the probability of a transition between states follows the discrete Weibull distribution.     

Bayesian inspection model with the negative binomial prior in the presence of inspection errors

One of the basic assumptions in Bayesian inspection models is that we have some prior knowledge about the number of defects in a certain product or software system. The prior knowledge can be often described as a probability distribution (e.g., Poisson distribution). In the paper, we propose three conditions that should be put forth as desirable properties for a prior probability distribution of the number of defects in the product. We review various prior probability distributions and test if they meet those conditions. The negative binomial distribution is found to be the only one that satisfies all the desirable conditions. With the negative binomial prior, we analyze the effects of various parameters on the Bayesian estimate of the number of undetected errors still remaining in the product.     

Technically optimal inspection policy with arithmetical adaption

A process is considered whose quality deteriorates accordingto a constant failure intensity . As in practice it can be difficultto estimate the true value of the purpose of this paper isto present a strategy which can be applied without knowing .In order to maximize the number of conforming items per timeunit perfect inspections and renewals are performed. The lengthof the inspection interval is described by an arithmetical sequenceand changes by the time depending on perceived assignable causes.Optimal adaptive control plans provide nearly the same performanceas in the case when is known.     

Economic optimization of off-line inspection in a process that also produces non-conforming units when in control and conforming units when out of control

A finite batch of units is produced by a process subject to random failures. The process starts from the in-control state and may shift, while producing a unit, to the out of control state. We consider the case that inspection is conducted after all the units of the batch have been produced, when the production order of the units is preserved. Most research has assumed that while in the in-control state, the process produces only conforming units and in the out of control state, it produces only non-conforming ones. In our research we relax this assumption, i.e. we consider that in the in-control state the process may also produce non-conforming units and in the out of control state, it may also produce conforming ones. Using dynamic programming, we develop an optimal inspection/disposition policy that finds which units to inspect and how to dispose of uninspected units in order to minimize the expected cost, which includes inspection and penalty costs due to classification errors. In addition to the optimal policy, we develop several heuristic policies since the computational complexity of the dynamic programming calculations is O(3^N)$\mathrm{O}(3^N)$. We then perform computational studies to check the behavior of the optimal and heuristic policies and also to compare the latter policies.     

Economic manufacturing quantity,optimum process mean,and economic specification limits setting under the rectifying inspection plan

Economic manufacturing quantity, process mean, and specification limits setting are three important methods for the inventory and quality control problems. In the imperfect production system, we usually consider the manufacturing quantity for reducing the inventory cost, determine the process level for reducing the production cost, and select the specification limits for screening the products. In this paper, we propose the above integrated model based on the application of rectifying inspection plan for obtaining maximum expected total profit of product. The asymmetric quadratic quality loss function is adopted for measuring the product quality. The sensitivity analyses of parameters are provided for illustration.     

自动检测中的经济设计问题

本文提出了在自动检测的工艺过程中控制限Ｋ的经济设计方法。     

Economic design of attribute np control charts using a variable sampling policy

To use a control chart, the quality engineer should specify three decision variables, namely the sample size, the sampling interval and the critical region of the chart. A significant part of recent research relaxed the constraint of using fixed design parameters to open the way to a new type of control charts called adaptive ones where at least one of the decision variables may change in real time based on the last data information. These adaptive schemes have proven their effectiveness from economical and statistical point of views. In this paper, the economic design of an attribute np control chart using a variable sampling interval (VSI) is treated. A sensitivity analysis is conducted to search for optimal design parameters minimizing the expected total cost per hour and to reveal the impact of the process and cost parameters on the behavior of optimal solutions. An economic comparison between the classical np chart, variable sample size (VSS) np control chart and VSI chart is conducted. It is found that switching from the classical attribute chart to the VSI sampling strategy results in notable cost savings and in reduction of the average time to signal and the average number of false alarms. In most cases of the sensitivity analysis, the VSI np chart outperforms the VSS np chart based on economical and statistical considerations. Copyright © 2014 John Wiley & Sons, Ltd.