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All Journal Pattimura International Journal of Mathematics (PIJMath)
Marsono Marsono
Badan Pusat Statistik (BPS) of West Sulawesi, Indonesia
Mathematics

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Application of Demerit Chart and Fuzzy Demerit Chart for Monitoring Paper Production M. Y. Matdoan; A. H. Talakua; Marsono Marsono; D. A. Safira; A. S. Suriaslan; M. Zulfadhli; A. W. Rukua
Pattimura International Journal of Mathematics (PIJMath) Vol 3 No 2 (2024): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol3iss2pp77-86

Abstract

Statistical Process Control (SPC) is an important method in quality control to monitor and improve production processes. Control charts are one of the SPC tools that are often used to quickly detect the causes of process variation so that improvements can be made before more nonconforming products are produced. The u chart is commonly used to monitor the number of defects in a production unit. However, this control chart has limitations in handling variations in defect severity, so demerit and fuzzy demerit control charts were developed to assign weights to defects based on their severity. Demerit and fuzzy demerit control charts have been applied in various production cases, but the study of the application of demerit and fuzzy demerit control charts in the industrial field, especially the paper industry, has never been done. The purpose of this study is to apply demerit and fuzzy demerit control charts to monitor and evaluate the quality of the paper production process at PT. Bosowa Media Grafika (Tribun Timur). The data used in this study are secondary data obtained from research conducted by Ilham (2012). The results obtained that the demerit chart and the fuzzy demerit chart show that the paper production process at PT Bosowa Media Grafika (Tribun Timur) is still in a stable condition (incontrol) in each observation. This shows that demerit and fuzzy demerit control charts have the same performance in monitoring the paper production process.
Co-Authors A. H. Talakua A. S. Suriaslan A. W. Rukua D. A. Safira M. Y. Matdoan M. Zulfadhli