Abstract

Statistical process control (SPC) charts are important tools for detecting process shifts. The control chart is an important statistical technique that is used to monitor the quality of a process. Shewhart control charts help to detect larger shifts in the process parameters, but Cumulative Sum (CUSUM) and Exponentially Weighted Moving Average (EWMA) charts are expected for smaller and moderate changes. The CUSUM control chart is normally used in industry for the result of small and moderate shifts in process spot and disparity. It can be shown that if there are sharp, irregular changes to a process, these types of charts are highly effective. On the other hand, if one involved in a small, persistent shift in a process, other types of control charts may be chosen, for instance the CUSUM control chart, originally developed by Page (1954). In this article, we used CUSUM control chart for monitoring the moisture level of the paper sheet.

Highlights

  • A most important purpose for a product or a process control is to constantly look up its quality

  • That Cumulative Sum (CUSUM) control chart is used to detect the smaller shift in the process if there is anything in the process

  • This paper discussed the problem based on monitoring the moisture level in the paper sheet material using the traditional and CUSUM control chart

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Summary

Introduction

A most important purpose for a product or a process control is to constantly look up its quality This aim, in statistical terms, may be expressed as variability reduction. Shewhart type charts are used to detect large shifts in a process whereas CUSUM and EWMA charts are known to be fast in detecting small to moderate shifts. A minor drifting in the process mean will direct to steadily rising or declining cumulative deviation value, Owing to the factor that it is cumulative. CUSUM control chart consider being more efficient in detecting small shift in the mean of a process. CUSUM control chart is comparatively slow to respond to large shift and firm to detect and analyse special trend patterns

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