Rich Industry

Rich Products, a food manufacturer from Upstate New York, recently utilized statistics to determine the right ingredients to make their frozen bread. With the popularity of their conventional bread dough's, there started to be a high demand for the company to produce a frozen bread dough. The problem however, was that the frozen dough was not coming out to the same taste level of its conventional counterpart. Once it identified a number of possible natural ingredients, the company then faced the difficult task of optimizing the amount of each ingredient in order to meet specified requirements for flavor, appearance, and softness, among other qualities. Through product experimentation, the company could fine tune the ingredients to find the right mixture, however the downside for this test is it can be extremely costly and lengthy. The company decided to turn to its food scientist, Sachin Bhatia, to figure out an easier less time consuming method. Bhatia turned to Design of Experiment (DOE) to find the right ingredient.

DOE techniques enables statisticians to determine simultaneously the individual and interactive effects of many factors that could affect the output results in whatever is being evaluated. By utilizing DOE, Rich was able to find the exact recipe needed to successfully produce their frozen dough. Let me now explain how they were able to do this through a statistical approach, rather than producing hundreds batches of dough.

Bhatia selected the D-optimal design because it provides the minimal number of blends ideally formulated to fit a given predictive model. He picked four different natural ingredients to include in the formulation of the new bread dough. The minimum value of each ingredient was set at zero to allow the experiment to explore the option of removing each ingredient from the recipe. Bhatia selected a quadratic model, which includes the non-linear blending terms for detection of component combinations that may be...