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All Journal Journal of Multidisciplinary Science: MIKAILALSYS Asian Journal of Science, Technology, Engineering, and Art Mikailalsys Journal of Advanced Engineering International Mikailalsys Journal of Mathematics and Statistics International Journal of Education, Management, and Technology Journal of Statistics and Data Science
Ayenigba, Alfred Ayo
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Agriculture, Biological Sciences & Forestry Arts Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Other

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Journal : Journal of Statistics and Data Science

 1 
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.
A Review of the Convolution of Geometric Distributions and Its Properties Ayenigba, Alfred Ayo; Afariogun, David; Olajide Oyewole , AGBOOLA; Ivande , James Serumun
Journal of Statistics and Data Science Vol. 5 No. 1 (2026)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v5i1.46545

Abstract

This review explores the convolution of geometric distributions, a key operation in probability theory for deriving the distribution of the sum of independent random variables. Geometric distributions quantify the number of Bernoulli trials needed for the first success and are foundational in discrete probability models. Convolving multiple geometric distributions with a common success probability produces a negative binomial distribution, modelling the number of trials needed to achieve a given number of successes. We present a concise derivation of this result, highlighting the relationship between geometric and negative binomial distributions. The review also outlines essential properties of the negative binomial distribution, including its mean, variance, moment-generating function, and some applications.
Co-Authors Afariogun, David Afariogun, David Adebisi Aina, Oluwaseun Ayomikun Aina, Oluwaseun Ayomiposi Ajao, Olutunde Michael Augustine, Chinenmerem Darlington Igbobie, Emeka Joseph Ivande , James Serumun Ogunkoya, C. O. Olajide Oyewole , AGBOOLA OYEDIRAN, Hakeem Makanjuola Taiwo, O. Esther