Exercise 15

1. Exercise 15

2. No.1 • (Worse) Incomplete data is commonly referred to as censored data and often occurs when the response variable is time to failure, e.g., accelerated life testing. • (Better 1) Incomplete data, commonly referred to as censored data, often occurs when the response variable is time to failure, e.g., accelerated life testing.

3. No.1 (cont.) • (Better 2) Commonly referred to as censored data, incomplete data often occurs when the response variable is time to failure, e.g., accelerated life testing.

4. No.2 • (Worse) Their method suggested either using iterative least squares (ILS) to analyze censored data or the initial fit is used to estimate the expected failure time for each censored observation. • (Better) 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.

5. No.3 • (Worse) 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. • The TOPSIS value in the ith trial is set to the designated value. • The factor effects based on the TOPSIS value are estimated. • Determine the optimal control factors and their levels.

6. No.3 (cont.) • (Better) 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 the TOPSIS value. • Determine the optimal control factors and their levels.

7. No.4 • (Worse) The system manager is in no case responsible for combining the experimental design techniques with quality loss considerations and careful consideration of how the various factors affect performance variation. • (Better) The system 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.

8. [Note 4.19] • Avoid wordiness by saying never instead of in no cases.

9. No.5 • (Worse) Herein, TOPSIS is applied to reduce the computational complexity, satisfy Taguchi’s quality’s loss, and finding a performance measurement index for each trial. • (Better) Herein, TOPSIS is applied to reduce the computational complexity, satisfy Taguchi’s quality’s loss, and find a performance measurement index for each trial.

10. No.6 • (Worse) The proposes procedure is employed for transformation of relative importance of each response, to compute the quality loss, determination of the TOPSIS value, to select the optimal factor/lever combination, and analysis of a confirmation experiment. • (Better) The proposes procedure is employed to transform relative importance of each response, compute the quality loss, determine the TOPSIS value, select the optimal factor/lever combination, and analyze a confirmation experiment.

11. No.7 • (Worse) The engineer makes an adjustment of the processing parameters and that the shop floor layout is finalized. • (Better) The engineer adjusts the processing parameters and finalizes the shop floor layout.

12. No.8 • (Worse) The proposed mechanism is adaptive, flexible, efficient, and can be applied in a factory setting. • (Better) The proposed mechanism is adaptive, flexible, efficient, and applicable in a factory setting.

13. No.9 • (Worse) This section not only presents a numerical example, but also the effectiveness of the proposed GA-based procedure for cell formation problems is demonstrated. • (Better) This section not only presents a numerical example, but also demonstrates the effectiveness of the proposed GA-based procedure for cell formation problems.

14. No.10 • (Worse) The censored data contain less information than complete data and analysis is made more difficult to perform. • (Better 1) The censored data contain less information than complete data and make analysis more difficult to perform. • (Better 2) The censored data is less than complete, making analysis difficult to perform.

15. No.11 • (Worse) The proposed model not only performs diagnostic checking, but also the optimal factor/level combination is determined. • (Better) The proposed model not only performs diagnostic checking, but also determines the optimal factor/level combination.

16. No.12 • (Worse) 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. The factor effects are plotted and the main effects on MRSN are tabulated. • B. Plot the factor efforts and tabulate the main effects on the mean response for nominal-the-best case. • Step 2: The optimal control factors and their levels are determined. • A. Find the control factor that significantly affects MRSN. • B. The optimum level for each control factor is determined. • Step 3: The optimal adjustment factors are determined.

17. No.12 (cont.) • (Better) 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 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 is. • Step 3: Determine the optimal adjustment factors.