Application of Statistical Quality Control to Production Management in Flour Milling Companies in Lagos State

This study applies statistical quality control techniques to production management challenges in flour milling companies operating in Lagos State, South West Nigeria, with a focus on improving process consistency and reducing product non-conformance rates. The flour milling industry is a critical node in Nigeria's food supply chain, and quality management failures carry significant public health and commercial consequences. The study employs a combination of control chart analysis, process capability assessment, and acceptance sampling to audit quality management systems at two flour milling facilities in the Apapa and Tin Can Island industrial areas of Lagos. Production data including moisture content, protein percentage, ash content, and particle size distribution of milled flour are collected over an eight-week monitoring period, and X-bar, S, and CUSUM control charts are constructed for each quality parameter. Process capability ratios are computed and benchmarked against the West African Standards Organisation's flour quality specifications. The study identifies process improvement opportunities through Pareto analysis of non-conformance categories and root cause analysis of out-of-control signals. Results reveal that moisture content and particle size distribution are the most frequently out-of-control quality characteristics, attributable to ageing temperature and humidity control systems. The study recommends the adoption of real-time sensor-based monitoring integrated with statistical process control software. Professional development implications for mathematics-trained quality managers are discussed. Keywords: statistical quality control, control charts, flour milling, process capability, Lagos