Comparison of bootstrap and asymptotic confidence limits for control charts in batch MSPC strategies

• New bootstrap CLs based are suggested for control charts in PCA-based batch MSPC.
• OTI and OTII errors were used to compare bootstrap CLs with asymptotic CLs.
• Comparison was done for five MSPC strategies by using simulated and real data.
• Bootstrap CLs for SPE-chart perform as good as the most accurate asymptotic CLs.
• Bootstrap CLs for D-chart outperform the asymptotic CLs.

The assumptions made to estimate confidence limits for control charts in MSPC based on asymptotic statistical distributions do not always hold. This mismatch can cause the limits to be unrealistic in both an optimistic (limits estimated too wide for the process under monitoring, not detecting true process upsets) and pessimistic (too narrow, raising false alarms) direction. New bootstrap confidence limits based on prediction are suggested for the control charts in different online PCA-based batch MSPC strategies as an alternative to asymptotic methods. Performance of the bootstrap and asymptotic confidence limits for five commonly applied methods are compared based on Overall Type I and II errors. A simulated bio-production batch process will be used to evaluate the theoretical performance of different monitoring schemes while the everyday potential is assessed by a real data industrial batch process dataset.