Application of Statistical Process Control in a Flour Milling Company in Kaduna State

Statistical process control provides quantitative tools for monitoring and improving manufacturing process stability, enabling food processors to reduce variability, minimise waste, and consistently meet product specifications. This study applies statistical process control techniques to the milling and sifting stages of a medium-scale flour milling company in Kaduna, North West Nigeria. Process data including particle size distribution, moisture content, ash content, and gluten strength were collected from 25 production days. Control charts, specifically X-bar and R charts for continuous variables and p-charts for attribute data, were constructed for each quality parameter. Process capability indices (Cp and Cpk) were calculated to quantify the ability of the process to consistently meet specifications. Results indicated that moisture content was in statistical control but with a Cpk of 0.85, indicating inadequate process capability. Particle size distribution showed multiple out-of-control signals attributable to screen wear and inconsistent feed rate. An Ishikawa fishbone analysis identified feed moisture variability and screen maintenance frequency as the primary root causes. Corrective actions including moisture conditioning of incoming wheat and a preventive maintenance schedule for milling screens were implemented over a 30-day trial period, resulting in a Cpk improvement to 1.12 for particle size. The study draws on recent statistical process control literature for food manufacturing. Findings provide a replicable quality improvement model for Nigerian flour mills. Keywords: statistical process control, flour milling, process capability, quality improvement, Kaduna State