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A Diagnostic Approach Using Statistical Quality Control Tools for Root Cause Identification of Ceramic Glaze Defects Ayenigba, Alfred Ayo; Taiwo, O. Esther; OYEDIRAN, Hakeem Makanjuola
Journal of Statistics and Data Science Vol. 4 No. 2 (2025)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v4i2.44795

Abstract

This study applies statistical quality control (SQC) tools to address glaze defects and strengthen process stability in the production of artisan ceramic mugs at Artisan Mugs Inc., with particular focus on the “Midnight Blue” product line. A Pareto analysis of 300 defective units identified glaze imperfections as the most frequent issue (54%), followed by handle cracks (21.7%). Root cause analysis using a fishbone diagram revealed multiple contributing factors spanning materials (e.g., elevated glaze viscosity), manpower (e.g., insufficient operator training), methods, machinery, measurement practices, and environmental conditions. To evaluate process stability, and R control charts were constructed from 25 production batches. Both charts demonstrated statistical control with no evidence of assignable causes, further validated by runs tests (). Process capability analysis indicated adequate but improvable performance, with indices of and for means, and and for ranges. These findings confirm that the process is stable, yet improvements are needed in centering and reducing variability.