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Title: Estimating Alarm Thresholds for Process Monitoring Data under Different Assumptions about the Data Generating Mechanism

Process monitoring (PM) for nuclear safeguards sometimes requires estimation of thresholds corresponding to small false alarm rates. Threshold estimation dates to the 1920s with the Shewhart control chart; however, because possible new roles for PM are being evaluated in nuclear safeguards, it is timely to consider modern model selection options in the context of threshold estimation. One of the possible new PM roles involves PM residuals, where a residual is defined as residual = data โˆ’ prediction. This paper reviews alarm threshold estimation, introduces model selection options, and considers a range of assumptions regarding the data-generating mechanism for PM residuals. Two PM examples from nuclear safeguards are included to motivate the need for alarm threshold estimation. The first example involves mixtures of probability distributions that arise in solution monitoring, which is a common type of PM. The second example involves periodic partial cleanout of in-process inventory, leading to challenging structure in the time series of PM residuals.
 [1] ;  [1] ;  [2] ;  [1] ;  [1] ;  [1]
  1. Statistical Sciences, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
  2. Mechanical Engineering Department, University of Glasgow, Glasgow G12 8QQ, UK
Publication Date:
Published Article
Journal Name:
Science and Technology of Nuclear Installations (Print)
Additional Journal Information:
Journal Name: Science and Technology of Nuclear Installations (Print); Journal Volume: 2013; Related Information: CHORUS Timestamp: 2017-06-21 11:18:03; Journal ID: ISSN 1687-6075
Hindawi Publishing Corporation
Sponsoring Org:
USDOE National Nuclear Security Administration (NNSA)
Country of Publication:
OSTI Identifier: