# Robust Adaptive Control Charts

## TL;DR

This paper proposes robust adaptive control charts that maintain effective process monitoring even when assumptions like normality and independence are violated, addressing the trade-off between robustness and detection delay.

## Contribution

It introduces a novel adaptive approach to robust control charts, reducing detection delays caused by robustness features in statistical process control.

## Key findings

- Enhanced robustness against assumption violations
- Reduced detection delay with adaptive methodology
- Improved false signal control

## Abstract

In statistical process control, procedures are applied that require relatively strict conditions for their use. If such assumptions are violated, these methods become inefficient, leading to increased incidence of false signals. Therefore, a robust version of control charts is sought to be less sensitive with respect to a breach of normality and independence in measurements. Robust control charts, however, usually increase the delay in the detection of assignable causes. This negative effect can, to some extent, be removed with the aid of an adaptive approach.