Systematic Statistical-Based Approach for Product Design: Application to Disinfectant Formulations

Product formulation development is a difficult and challenging task. The challenges include modeling complex systems and chemicals. Various tests are performed, often on a trial and error basis, to evaluate the performance of the prototypes in the product development process. These tests can be very expensive and time-consuming. A methodology is presented to shorten the product development time and reduce the costs given a database of historical data. It is based Oil augmenting the existing data set through designed experiments. Ail empirical model is first developed by analyzing the augmented data set using least-squares regression analysis. The model is then inverted by using an optimization technique, and the product formulation can be predicted on the basis of the desired product specifications. Ail iterative, sequential approach is employed in which the knowledge gained at each stage is applied in a systematic manner to design further experiments so that the future efforts will need fewer trials. This methodology is illustrated by a case study of disinfectant formulations and is proven to be Superior to conventional formulation design methods. These disinfectant formulations consist of primarily water and small amounts of surfactants, oxidizing agents, chelating agents, pH buffers, and pH adjusters and consequently the resulting products are clear liquids. Although the methodology is illustrated oil disinfectant product development, it is introduced in this paper in a general way and call be implemented in other applications.