测试能力指标cpk及其在汽车发动机制造业中的应用

IF 1.3 4区工程技术 Q4 ENGINEERING, INDUSTRIAL

Quality Engineering Pub Date : 2023-01-02 DOI:10.1080/08982112.2022.2087042

H. Iranmanesh, A. Parchami, M. Jabbari Nooghabi

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引用次数: 1

摘要

假设检验是过程能力决策的一种有效方法。即使在正态分布下，基于确定其自然估计量分布的检验逆境也是非常复杂的。因此，蒙特卡罗模拟方法是一种基于自然估计量的假设检验的可执行过程。该方法是一种评估产品质量是否满足预先设定的规格限制的测试技术。这个程序意味着蒙特卡罗统计检验，这是适用于正常过程。以某汽车制造厂为例，对产品进行了检验，并通过数值计算说明了蒙特卡罗临界值对假设检验的可靠决策的影响

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Testing capability index C pk with its application in automobile engine manufacturing industry

Abstract Hypotheses testing is an effective technique for making a decision about the process capability. The adversity to test based on determining the distribution of its natural estimator is very complex, even under the Normal distribution. Thus, the Monte Carlo simulation approach is an executable procedure for the hypotheses testing of based on the natural estimator. The proposed approach is a testing technique to evaluate whether products quality meets the preset specification limits. This procedure implies a Monte Carlo statistical test, which is applicable to Normal processes. A case study in an automobile factory is presented to check out the products, and numerical computations are presented to show the effect of the Monte Carlo critical values for making a reliable decision on the hypotheses testing of

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来源期刊

Quality Engineering ENGINEERING, INDUSTRIAL-STATISTICS & PROBABILITY

CiteScore

3.90

自引率

10.00%

发文量

审稿时长

>12 weeks

期刊介绍： Quality Engineering aims to promote a rich exchange among the quality engineering community by publishing papers that describe new engineering methods ready for immediate industrial application or examples of techniques uniquely employed. You are invited to submit manuscripts and application experiences that explore: Experimental engineering design and analysis Measurement system analysis in engineering Engineering process modelling Product and process optimization in engineering Quality control and process monitoring in engineering Engineering regression Reliability in engineering Response surface methodology in engineering Robust engineering parameter design Six Sigma method enhancement in engineering Statistical engineering Engineering test and evaluation techniques.