Comparison of flour mill stream blending approaches: Linear programming versus ash curve

Abstract

Background and objectives Flour millers often produce several flour types from a single wheat grist. Consequently, different specifications characterize each flour. For example, French standards specify six different flour types, each classified by ash content. The proportional blending of different flour streams from a single wheat grist achieves the target flour specifications. This study explores the opportunity to improve flour blending using linear programming and compares it to sequential ash curve blending. Findings Linear programming and ash curve approaches were used to meet specifications for French flour types from a wheat grist milled to produce 10 flour streams, each stream having different flour quality attributes. The first simulation set quantity targets for Types 45, 55, and 65 flour. The balance of the flour went to the lower value Types 80, 110, and 150. The flour type targets were met using Linear Programming. By utilizing the ash curve method, Type 65 flour was under‐delivered. The second simulation aimed to maximize income using the two methods with no constraints on the amount of each flour type. The linear programming approach resulted in a 0.13% increase in revenue compared to the ash curve technique. Conclusion In the first simulation, the linear programming technique reduced the lower‐value high ash flour types, generating an additional $6.16/ton of flour. In the second simulation, linear programming increased income by $0.84/ton of flour. Thus, a milling plant operating for 8,000 hr/year and processing 20 tons of wheat/hr translates to $779,000 and $107,000 per annum, respectively. Significance and novelty This study showed that linear programming could significantly improve flour blending outcomes, resulting in increased profitability and resource utilization in the milling industry.