Probability and Statistics in Quality Assurance for Cement Production in Lafarge Africa, Ewekoro

This study applies probability theory and inferential statistics to quality assurance challenges in cement production at the Lafarge Africa manufacturing plant in Ewekoro, Ogun State, South West Nigeria, one of the country's largest cement producers. Quality assurance in cement manufacturing is governed by the Standards Organisation of Nigeria's industrial standard for Portland cement, and statistical methods provide the quantitative framework for determining whether production processes are consistently meeting specification limits for compressive strength, setting time, fineness, and chemical composition. Production quality data comprising daily laboratory test results for clinker and finished cement over a 24-month period are obtained under a research collaboration agreement, covering a combined dataset of approximately 3,600 test observations. Probability distribution fitting is applied to characterise the statistical behaviour of each quality parameter, and hypothesis tests are conducted to detect systematic shifts in mean quality levels across production shifts, kiln lines, and raw material batches. Analysis of variance is used to partition quality variation into assignable sources, and regression analysis identifies raw material composition variables that most strongly predict finished cement quality outcomes. Results reveal statistically significant quality differences across the two production lines attributable to differential maintenance cycles, and a significant predictive relationship between limestone calcium carbonate content and clinker quality. Keywords: statistical quality assurance, cement production, probability distributions, analysis of variance, Lafarge Africa