Constructing a Sample-Size Adaptable Sampling System Based on a Third-Generation Process Capability Index

IF 1.5 4区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
To-Cheng Wang
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引用次数: 0

Abstract

Acceptance sampling plans (ASP) help practitioners economically and efficiently verify product quality, serving as a widely applied statistical quality control method. Among ASPs, the simplest form is the single sampling plan (SSP). Recently, acceptance sampling systems incorporating two SSPs as decision rules for lot disposition have gained significant attention due to their superior performance. Depending on the switching mechanism for decision rules, acceptance sampling systems can be categorized into quick switching systems and two-plan sampling systems (TSS), where TSS exhibits greater flexibility and adaptability in its rule-switching mechanism. In this study, we construct a TSS with a sample size adjustment mechanism and integrate it with a third-generation process capability index. Detailed investigation and analysis reveal that the proposed method provides more substantial incentives for suppliers, as its properties penalize suppliers who submit poor-quality lots through increased sample size while rewarding suppliers who submit high-quality lots by requiring smaller sample sizes. Finally, we demonstrate the application of the proposed method through a practical case study.

基于第三代过程能力指标的样本容量自适应抽样系统的构建
验收抽样计划(ASP)是一种广泛应用的统计质量控制方法,可以帮助从业者经济有效地验证产品质量。在asp中,最简单的形式是单采样计划(SSP)。最近,采用两个ssp作为批次配置决策规则的验收抽样系统由于其优越的性能而获得了极大的关注。根据决策规则切换机制的不同,验收抽样系统可分为快速切换系统和双计划抽样系统,其中双计划抽样在规则切换机制上表现出更大的灵活性和适应性。在本研究中,我们构建了一个带有样本大小调整机制的TSS,并将其与第三代过程能力指标相结合。详细的调查和分析表明,该方法为供应商提供了更大的激励,因为其特性通过增加样本量来惩罚提交质量差的供应商,而通过要求较小的样本量来奖励提交高质量批次的供应商。最后,我们通过一个实际案例来说明该方法的应用。
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来源期刊
CiteScore
2.70
自引率
0.00%
发文量
67
审稿时长
>12 weeks
期刊介绍: ASMBI - Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis) was first published in 1985, publishing contributions in the interface between stochastic modelling, data analysis and their applications in business, finance, insurance, management and production. In 2007 ASMBI became the official journal of the International Society for Business and Industrial Statistics (www.isbis.org). The main objective is to publish papers, both technical and practical, presenting new results which solve real-life problems or have great potential in doing so. Mathematical rigour, innovative stochastic modelling and sound applications are the key ingredients of papers to be published, after a very selective review process. The journal is very open to new ideas, like Data Science and Big Data stemming from problems in business and industry or uncertainty quantification in engineering, as well as more traditional ones, like reliability, quality control, design of experiments, managerial processes, supply chains and inventories, insurance, econometrics, financial modelling (provided the papers are related to real problems). The journal is interested also in papers addressing the effects of business and industrial decisions on the environment, healthcare, social life. State-of-the art computational methods are very welcome as well, when combined with sound applications and innovative models.
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