Adjustment of Measurement Error Effects on Dispersion Control Chart with Distribution-Free Quality Variable

In industrial processes, control charts are useful tools to monitor the quality of products and detect possibly out-of-control processes. While many types have been available for data analysts, they were developed by assuming that variables precisely measured. applications, however, measurement error is ubiquitous when falsely recorded investigators or imprecisely collected unadjusted machines. Even though impacts different explored, error-corrected still unavailable. this study, we propose a new dispersion chart with correction fill out research gap. Our key idea convert observed distribution-free process into flexible sign statistic, then adopt function adjust effects on statistic. Finally, develop an exponentially weight-moving average based corrected The proposed not only eliminates effects, but also provides more reliable limits monitoring dispersion. Throughout numerical examination, find effective in handling moderate large levels shows good detection performance. implemented semiconductor data.