(104b) Considerations for Product Development Model Formulations in Constrained Optimization Problems

For manufacturers, the continuous development of new products is necessary to remain competitive, whether it is to reduce cost, utilize alternative materials, or to meet new regulations. A design-of-experiments approach may not be the most effective tool to explore formulation options, especially for products that contain many ingredients and properties. Instead, to capitalize on data collected during product development, multivariate analysis (MVA) can be used to build a model to predict final product quality based on ingredient mixture properties, along with other fundamental knowledge.

In tandem with these statistical models, there are factors to consider that may not be captured in the model correlation structure, such as the importance of cost and quality, the introduction of new ingredients, and constraints on ingredient ratios, classes, and mixture properties. In order to explore solutions of this multifaceted problem, a projection onto latent structures (PLS) model is trained and embedded in a nonlinear constrained optimization problem.

This presentation will provide a walkthrough of the embedded optimization problem, how modeling decisions are considered in the formulation, and practical solution approaches.