Experimental Design for Optimizing the Cleaning of Starch Adhering to Stainless‐Steel Surfaces Using Nonionic Surfactants and Silica Microparticles

Abstract

The statistical design of experiments has been used to assess the detergency of starch adhering to stainless steel considering three factors: pH, flow rate, and concentration of silica particles in the cleaning solution. The cleaning tests were carried out in a continuous‐flow device that simulates the behavior of a Cleaning‐In‐Place washing system. Different statistical designs were used to evaluate the detergency of cleaning solutions in the absence of surfactants and with two nonionic surfactants, i.e., an ethoxylated alcohol, and an alkylpolyglucoside (APG). Expressions were developed to simulate detergency levels as a function of the variables assayed, determining the optimal detergency of each cleaning solution studied. The results indicate that the variable most influential on detergency was pH. Cleaning solutions with high alkalinity are required to achieve a significant cleaning efficiency. On the other hand, the silica‐particle concentration did not influence the detergency results using cleaning solutions without surfactants. Nevertheless, the addition of either the ethoxylated alcohol or the APG to the cleaning solution with silica particles has a significant effect on detergency: it diminished with the ethoxylated alcohol and increased with the APG. Maximum detergency was found at the highest level of pH, particle concentration, and flow rate when the APG was added to the cleaning solution.