An Application X-bar Chart and Statistical Process Control With R Package

Quality control is a critical aspect of ensuring that production processes meet established standards and customer requirements. One widely used approach in Statistical Quality Control (SQC) is the control chart, particularly the X̄ and s charts, which monitor process stability based on the mean and variability of the data. This study aims to evaluate the quality and variation of the feed water boiler process using X̄ and s control charts, as well as to assess process capability with the aid of the R programming language and the qcc package. The dataset comprises hardness measurements of water collected over 25 consecutive days, three times per day, resulting in 75 observations. Initial analysis revealed one data point outside the control limit in the X̄ chart, which, when excluded, improved overall process stability. The s chart indicated more consistent stability compared to the X̄ chart. Process capability analysis yielded Cp and Cpk values of 0.5844 and 0.5600, respectively, indicating that the process is not yet capable of fully meeting product specifications and exhibits relatively high variability.These findings highlight the need for process improvement through variation reduction and six sigma approaches.The use of R/qcc proved to be an effective tool for monitoring and analyzing quality control in production processes.

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Publication Details

Journal
UNP Journal of Statistics and Data Science
Published
2025-05-31
DOI
https://doi.org/10.24036/ujsds/vol3-iss2/363
Primary Topic
Advanced Statistical Process Monitoring
Type
article
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article

An Application X-bar Chart and Statistical Process Control With R Package

Yenni Kurniawati, Niswatul Rizkiah
UNP Journal of Statistics and Data Science
Advanced Statistical Process Monitoring
article

An Application X-bar Chart and Statistical Process Control With R Package

Yenni Kurniawati, Niswatul Rizkiah
article en

Abstract

Quality control is a critical aspect of ensuring that production processes meet established standards and customer requirements. One widely used approach in Statistical Quality Control (SQC) is the control chart, particularly the X̄ and s charts, which monitor process stability based on the mean and variability of the data. This study aims to evaluate the quality and variation of the feed water boiler process using X̄ and s control charts, as well as to assess process capability with the aid of the R programming language and the qcc package. The dataset comprises hardness measurements of water collected over 25 consecutive days, three times per day, resulting in 75 observations. Initial analysis revealed one data point outside the control limit in the X̄ chart, which, when excluded, improved overall process stability. The s chart indicated more consistent stability compared to the X̄ chart. Process capability analysis yielded Cp and Cpk values of 0.5844 and 0.5600, respectively, indicating that the process is not yet capable of fully meeting product specifications and exhibits relatively high variability.These findings highlight the need for process improvement through variation reduction and six sigma approaches.The use of R/qcc proved to be an effective tool for monitoring and analyzing quality control in production processes.

UNP Journal of Statistics and Data ScienceVol. 3(2)
State University of Padang (ID)
Openalex Percentile: Top 88%
Advanced Statistical Process Monitoring
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