Case Study: Tate & Lyle Reduces Corn Sugar Particle Variation with Minitab

Tate & Lyle cuts corn sugar variation by nearly 50% with Minitab

Tate & Lyle, a global leader in the food and beverage industry, faced a challenge in optimizing its corn sugar crystallization process. The company needed to keep the particle size distribution of its sweeteners uniform to ensure the right taste and texture but struggled with over 1,000 interacting process variables causing unpredictable variation. They turned to Minitab for assistance, utilizing Minitab Statistical Software and Salford Predictive Modeler.

Using TreeNet within Minitab's Salford Predictive Modeler, Tate & Lyle was able to identify the eight key predictors responsible for nearly half of the variation in particle size. This solution provided by Minitab enabled them to understand the complex relationships between variables and find ways to control them. As a result, Tate & Lyle found effective strategies to significantly reduce the variation in their final product.

Tate & Lyle