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 ...view middle of the document...
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 significantly antagonistic (detrimental) or synergistic (beneficial). He set the four factors to the following:
A) Ingredient A, 0 to 2
B) Ingredient B, 0 to 4
C) Ingredient C, 0 to 0.04
D) Ingredient D, 0 to 2
The unit for each factor is flour percent or Baker’s percent which measures
the weight of the ingredient relative to the total weight of the flour. The total of the level of the factors was fixed at 4. Bhatia had the lab create XX amount of different samples, and then the samples were graded on in 10 different categories, based on the following guidelines:
3) Height of the bread after baking
4) Width of the bread after baking.
5) Overall likeability
6) Crust flavor
7) Crumb flavor
9) Cell size
10) Crumb density
Once Bhatia had all the grades from each sample, he recorded the data into the Design-Expert software, which produced a statistical analysis. After perfoming a ANOVA, Bhatia came up with 4 significant effects. With these 4 significant effects he was able to develop a desirability function that provided weights and constraints for the responses, which he used to optimize the factors. The Design-Expert software was then able to predict the desirability of each. After that he took the 4 selected samples that were with a significant desirability level and performed a second taste test, which ultimately verified what Design-Expert already solved. The highest one predicted by Design-Expert is the same set of ingredients you can buy in the store today.
By utilizing DOE, Rich saved time and money by successfully coming up with the right ingredients for their frozen bread dough. DOE is not a revolutionary concept as it has been around, however in this technological age, a simple mathematical solution can be utilized to perfect your product. DOE did just that for Rich's frozen bread dough.