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All Journal African Multidisciplinary Journal of Sciences and Artificial Intelligence Open Access DRIVERset Kwaghe International Journal of Sciences and Technology Open Access DRIVERset
Chinedu Samuel Onyedika
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Environmental Science Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Social Sciences

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Analysis of Variance in the Beverage Filling Process: An Application of One-Way ANOVA to Product Lines at Seven-Up Bottling Company, Kaduna, Nigeria Chinedu Samuel Onyedika
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 3 No 2 (2026): African Multidisciplinary Journal of Sciences and Artificial Intelligence
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/amjsai.v3i2.11205

Abstract

Consistency in beverage filling is essential for regulatory compliance, product quality, and consumer confidence, particularly in high-volume bottling operations involving multiple product lines. This study investigated whether mean net-content filling values differed significantly across five product lines—7UP, Mirinda Orange, Mountain Dew, Pepsi, and Teem Bitter Lemon—at the Seven-Up Bottling Company Kaduna Plant. Net-content filling data were collected during morning, afternoon, and night production shifts on selected production days between July and August 2021, yielding 75 observations, with 15 observations obtained for each product. A one-way analysis of variance was conducted to compare mean filling values across the five product lines, followed by Tukey simultaneous comparisons and Fisher individual tests for pairwise differences in means. The analysis revealed no statistically significant difference in mean filling values across the product lines, F = 0.30, p = .879, at α = .05. The post hoc analyses corroborated this result, as all adjusted pairwise p-values exceeded the .05 significance threshold. Accordingly, the null hypothesis that the five product lines had equal mean filling values was not rejected. These findings indicate that the filling process did not generate statistically different filling outcomes across product types during the study period. The observed filling-related variation is therefore more consistent with common-cause process variation than with product-specific assignable causes. The study contributes empirical evidence for strengthening statistical quality-control practices in beverage production and underscores the importance of continuous process monitoring to maintain net-content consistency across product lines.
Analysis of Variance in the Beverage Filling Process: An Application of One-Way ANOVA to Product Lines at Seven-Up Bottling Company, Kaduna, Nigeria Chinedu Samuel Onyedika
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 3 No 2 (2026): African Multidisciplinary Journal of Sciences and Artificial Intelligence
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/amjsai.v3i2.11205

Abstract

Consistency in beverage filling is essential for regulatory compliance, product quality, and consumer confidence, particularly in high-volume bottling operations involving multiple product lines. This study investigated whether mean net-content filling values differed significantly across five product lines—7UP, Mirinda Orange, Mountain Dew, Pepsi, and Teem Bitter Lemon—at the Seven-Up Bottling Company Kaduna Plant. Net-content filling data were collected during morning, afternoon, and night production shifts on selected production days between July and August 2021, yielding 75 observations, with 15 observations obtained for each product. A one-way analysis of variance was conducted to compare mean filling values across the five product lines, followed by Tukey simultaneous comparisons and Fisher individual tests for pairwise differences in means. The analysis revealed no statistically significant difference in mean filling values across the product lines, F = 0.30, p = .879, at α = .05. The post hoc analyses corroborated this result, as all adjusted pairwise p-values exceeded the .05 significance threshold. Accordingly, the null hypothesis that the five product lines had equal mean filling values was not rejected. These findings indicate that the filling process did not generate statistically different filling outcomes across product types during the study period. The observed filling-related variation is therefore more consistent with common-cause process variation than with product-specific assignable causes. The study contributes empirical evidence for strengthening statistical quality-control practices in beverage production and underscores the importance of continuous process monitoring to maintain net-content consistency across product lines.
Monitoring Carbonation Levels in Beverage Production Using X-Bar/R-Charts and Tabular CUSUM: A Statistical Process Control Study at Seven-Up Bottling Company, Kaduna, Nigeria Chinedu Samuel Onyedika
Kwaghe International Journal of Sciences and Technology Vol 3 No 2 (2026): Kwaghe International Journal of Sciences and Technology
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/kijst.v3i2.11203

Abstract

Carbonation is a defining sensory attribute of carbonated soft drinks and a critical determinant of product quality because carbon dioxide (CO₂) volume directly influences taste, perceived freshness, mouthfeel, and consumer acceptability. Deviations from specified carbonation levels can result in under-carbonated beverages that taste flat and stale or over-carbonated products characterized by excessive foaming, premature cap ejection, and potential bottle-integrity failures. Maintaining consistent CO₂ volume is particularly challenging in high-capacity bottling operations such as Seven-Up Bottling Company, Kaduna, which produces up to 800,000 bottles daily across multiple product types and bottle sizes. Carbonation levels may fluctuate because of variations in beverage temperature, syrup concentration, filling pressure, and machine calibration across production shifts. This study aims to evaluate the statistical stability of the carbonation process and distinguish common-cause variation from assignable-cause variation in CO₂ volume. A dataset comprising 30 production subgroups, generated through the facility’s 30-minute gas-volume monitoring procedure, was analyzed using Statistical Process Control techniques. The X-bar and R-chart combination was applied to assess process central tendency and dispersion, while the Cumulative Sum chart was used to detect small and persistent shifts that might not be readily identified through conventional control charts. The combined application of these methods provides a systematic framework for identifying abnormal carbonation patterns, supporting timely corrective action, and strengthening process-control decisions. This study contributes the first documented Statistical Process Control analysis of carbonation quality at the Kaduna facility and offers a practical basis for improving product consistency, reducing quality failures, and enhancing consumer acceptability in large-scale beverage production.
Monitoring Carbonation Levels in Beverage Production Using X-Bar/R-Charts and Tabular CUSUM: A Statistical Process Control Study at Seven-Up Bottling Company, Kaduna, Nigeria Chinedu Samuel Onyedika
Kwaghe International Journal of Sciences and Technology Vol 3 No 2 (2026): Kwaghe International Journal of Sciences and Technology
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/kijst.v3i2.11203

Abstract

Carbonation is a defining sensory attribute of carbonated soft drinks and a critical determinant of product quality because carbon dioxide (CO₂) volume directly influences taste, perceived freshness, mouthfeel, and consumer acceptability. Deviations from specified carbonation levels can result in under-carbonated beverages that taste flat and stale or over-carbonated products characterized by excessive foaming, premature cap ejection, and potential bottle-integrity failures. Maintaining consistent CO₂ volume is particularly challenging in high-capacity bottling operations such as Seven-Up Bottling Company, Kaduna, which produces up to 800,000 bottles daily across multiple product types and bottle sizes. Carbonation levels may fluctuate because of variations in beverage temperature, syrup concentration, filling pressure, and machine calibration across production shifts. This study aims to evaluate the statistical stability of the carbonation process and distinguish common-cause variation from assignable-cause variation in CO₂ volume. A dataset comprising 30 production subgroups, generated through the facility’s 30-minute gas-volume monitoring procedure, was analyzed using Statistical Process Control techniques. The X-bar and R-chart combination was applied to assess process central tendency and dispersion, while the Cumulative Sum chart was used to detect small and persistent shifts that might not be readily identified through conventional control charts. The combined application of these methods provides a systematic framework for identifying abnormal carbonation patterns, supporting timely corrective action, and strengthening process-control decisions. This study contributes the first documented Statistical Process Control analysis of carbonation quality at the Kaduna facility and offers a practical basis for improving product consistency, reducing quality failures, and enhancing consumer acceptability in large-scale beverage production.
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