編修英文 (Copyediting Skills)

[ Exercise 15 ]

  1. Incomplete data, commonly referred to as censored data, often occurs when the response variable is time to failure, e.g., accelerated life testing.
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  2. Their method suggested using either iterative least squares (ILS) to analyze censored data or the initial fit to estimate the expected failure time for each censored observation.
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  3. The TOPSIS value for each trial and the optimal factor/level combination can be determined in the following steps:
    Apply equations (4) ~ (8) to compute the relative closeness of each trial.
    Set the TOPSIS value in the ith trial to the designated value.
    Estimate the factor effects based on TOPSIS value.
    Determine the optimal control factors and their levels.
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  4. The systems manager is in no case responsible for combining the experimental design techniques with quality loss considerations and carefully considering how the various factors affect performance variation.
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  5. Herein, TOPSIS is applied to reduce the computational complexity, satisfy Taguchi's quality's loss, and find a performance measurement index for each trial.
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  6. The proposed procedure is employed to transform the relative importance of each response, compute the quality loss, determine the TOPSIS value, select the optimal factor/level combination, and analyze a confirmation experiment.
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  7. The engineer adjusts the processing parameters and finalizes the shop floor layout.
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  8. The proposed mechanism is adaptive, flexible, efficient, and applicable in a factory setting.
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  9. This section not only presents a numerical example, but also demonstrates the effectiveness of the proposed GA-based procedure for cell formation problems.
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  10. The censored data contain less information than complete data and make analysis more difficult to perform.
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  11. The proposed model not only performs diagnostic checking, but also determines the optimal factor/level combination.
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  12. The procedure to determine the optimal factor/level combination in a multi-response problem is described as follows:
    Step 1: Estimate the factor effects.
    A. Plot the factor effects and tabulate the main effects on MRSN.
    B. Plot the factor efforts and tabulate the main effects on the mean response for the nominal-the-best case.
    Step 2: Determine the optimal control factors and their levels.
    A. Find the control factor that significantly affects MRSN.
    B. Determine the optimum level for each control factor.
    Step 3: Determine the optimal adjustment factors.
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