Investigating the Effect of Small Sample Process Capability Index Under Different Bootstrap Methods

In the quality control of multi-variety and small-batch products, the calculation of the process capability index is particularly important. However, when the sample size is not enough, the process distribution cannot be judged, if the traditional method is still used to calculate the process capability index; there will be misapplication or misuse. In this paper, the Bootstrap method is introduced into the estimation of process capability index and the calculation of its confidence interval by using Standard Bootstrap (SB), Percentile Bootstrap (PB), Percentile-t Bootstrap (PTB) and Biased-corrected Percentile Bootstrap (BCPB) methods were used to analyze and compare the process capability index. It is found that in symmetric distribution, only the sample size has a significant effect on the length of the confidence interval；but in asymmetric distribution, sample size and Bootstrap methods are both significant factors affecting the length of confidence interval.

@article{Wang2024,
  title     = {Investigating the Effect of Small Sample Process Capability Index Under Different Bootstrap Methods},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {4},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Liyan Wang and Guihua Bo and Mingjuan Du},
  doi       = {10.14569/IJACSA.2024.0150457},
  url       = {https://doi.org/10.14569/IJACSA.2024.0150457}
}