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    Time Series Control Charts in the Presence of Model Uncertainty 

    Source: Journal of Manufacturing Science and Engineering:;2002:;volume( 124 ):;issue: 004:;page 891
    Author(s): Daniel W. Apley; Mem.; ASME
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Time series control charts are popular methods for statistical process control of autocorrelated processes. In order to implement these methods, however, a time series model of the process is ...
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    A Suboptimal N-Step-Ahead Cautious Controller for Adaptive Control Applications 

    Source: Journal of Dynamic Systems, Measurement, and Control:;1998:;volume( 120 ):;issue: 003:;page 419
    Author(s): Jianjun Shi; Daniel W. Apley
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: If there is little a priori knowledge of the plant parameters, the performance of certainty equivalence based adaptive controllers during the transient period, before the parameter estimates have ...
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    Singularity Issues in Fixture Fault Diagnosis for Multi-Station Assembly Processes 

    Source: Journal of Manufacturing Science and Engineering:;2004:;volume( 126 ):;issue: 001:;page 200
    Author(s): Yu Ding; Daniel W. Apley; Abhishek Gupta
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This paper presents a method of diagnosing variance components of process error sources in singular manufacturing systems. The singularity problem is studied and the cause examined in the context ...
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    Understanding the Effects of Model Uncertainty in Robust Design With Computer Experiments 

    Source: Journal of Mechanical Design:;2006:;volume( 128 ):;issue: 004:;page 945
    Author(s): Daniel W. Apley; Wei Chen; Jun Liu
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The use of computer experiments and surrogate approximations (metamodels) introduces a source of uncertainty in simulation-based design that we term model interpolation uncertainty. Most existing ...
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    Quantification of Model Uncertainty: Calibration, Model Discrepancy, and Identifiability 

    Source: Journal of Mechanical Design:;2012:;volume( 134 ):;issue: 010:;page 100908
    Author(s): Paul D. Arendt; Daniel W. Apley; Wei Chen
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: To use predictive models in engineering design of physical systems, one should first quantify the model uncertainty via model updating techniques employing both simulation and experimental data. ...
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    Improving Identifiability in Model Calibration Using Multiple Responses 

    Source: Journal of Mechanical Design:;2012:;volume( 134 ):;issue: 010:;page 100909
    Author(s): Paul D. Arendt; Daniel W. Apley; Wei Chen; David Lamb; David Gorsich
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In physics-based engineering modeling, the two primary sources of model uncertainty, which account for the differences between computer models and physical experiments, are parameter uncertainty ...
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