在运行测试中应用顺序分析的案例研究

IF 1.3 4区 工程技术 Q4 ENGINEERING, INDUSTRIAL
Monica Ahrens, Rebecca M. Medlin, Keyla Pagán-Rivera, John W. Dennis
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引用次数: 0

摘要

摘要序列分析涉及统计评估,其中数据的数量、模式或组成不是在调查开始时确定的,而是取决于调查期间获得的信息。尽管序列分析起源于国防部(DoD)的弹道学测试,并在其他学科中广泛使用,但在国防部却没有得到充分利用。扩大序列分析的使用可以节省资金并减少测试时间。在本文中,我们介绍了序列分析,描述了它在作战测试与评估(OT&E)中的当前和潜在用途,并提出了一种将其应用于防御系统测试与评估的方法。我们通过进行模拟研究并将该方法应用于案例研究来评估所提出的方法。此外,我们还讨论了OT&E中序列分析需要解决的挑战。最后,虽然操作测试是本文的重点,但所提出的方法适用于许多学科的实验和一般测试活动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Case study on applying sequential analyses in operational testing
Abstract Sequential analysis concerns statistical evaluation in which the number, pattern, or composition of the data is not determined at the start of the investigation, but instead depends on the information acquired during the investigation. Although sequential analysis originated in ballistics testing for the Department of Defense (DoD)and it is widely used in other disciplines, it is underutilized in the DoD. Expanding the use of sequential analysis may save money and reduce test time. In this paper, we introduce sequential analysis, describe its current and potential uses in operational test and evaluation (OT&E), and present a method for applying it to the test and evaluation of defense systems. We evaluate the proposed method by performing simulation studies and applying the method to a case study. Additionally, we discuss challenges to address for sequential analysis in OT&E. Lastly, while operational testing is the focus in this paper, the methodology presented is applicable to campaigns of experimentation and general testing across numerous disciplines.
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来源期刊
Quality Engineering
Quality Engineering ENGINEERING, INDUSTRIAL-STATISTICS & PROBABILITY
CiteScore
3.90
自引率
10.00%
发文量
52
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.
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