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A simulation comparison study for estimating the process capability index c∗pm with asymmetric tolerances.
| Content Provider | CiteSeerX |
|---|---|
| Author | Wu, Shu-Fei |
| Abstract | Process capability indices had been widely used to evaluate the process performance. The process capability index C∗pm proposed by Chan et al. [2] does take into account of the proximity of the process mean to the target value T for asymmetric tolerance. For point estimation of this index, a Jackknife method is presented to reduce bias. Five interval esti-mation methods for obtaining approximate confidence intervals are presented and compared. One is based on the chi-squared approximation to the distribution of the natural estimator of C∗pm given in Boyles [1], three are based on the bootstrap including standard bootstrap (SB), percentile bootstrap (PB) and bisaed-corrected percentile bootstrap (BCPB) and the last one is based on the Jackknife technique. A simulation comparison study of the perfor-mance of five methods is done under normal process environment and the results show that the Jackknife interval outperforms the other four methods. Boyles’s [1] confidence interval and the SB confidence interval are more reliable than the PB and BCPB methods. At last, one real life example is used to demonstrate the use of the confidence interval to decide if the process is capable. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Simulation Comparison Study Asymmetric Tolerance Process Capability Index Pm Confidence Interval Process Capability Index Jackknife Technique Approximate Confidence Interval Interval Esti-mation Method Process Performance Percentile Bootstrap Target Value Process Mean Bisaed-corrected Percentile Bootstrap Chi-squared Approximation Last One Normal Process Environment Jackknife Interval Standard Bootstrap Natural Estimator Point Estimation Real Life Example Bcpb Method Sb Confidence Interval Jackknife Method |
| Content Type | Text |
