A Robust Design Criterion for Synthesis, Characterization and Quality Control of Nanoparticles - a Fuzzy Mathematical Approach

In this paper we present the aspects of statistical quality control for modelling a process of nanoparticles (NPs) preparation, providing feedback on the production and formulation processes in controlled manner. An in process sample preparation and particle sizing system using image processing and Dutta Majumder’s generalized shape theory was developed to analyze the particle shape based properties that characterize the synthesis process. The continuous process of improvements will ultimately decrease costs and improve performance of the production system and the product. We have showed that both the nano technology based industry achieves its customers benefit from proper quality control of the process. The particle shape contours were measured using transmission electron microscope to quantify the NPs sphericity. Fuzzy based clustering is used to study the Transmission Electron Microscope image of NPs. To meet the design specification of NPs synthesis under statistical quality control, process capability ratio up to 1.5 gives good results. The results are validated with chemical analysis. This type of characterization helps the researchers in size-based spectral tuning, biological labelling, and toxicity studies and suggests general protocols to address these problems. Keywords— Nano Synthesis, Fuzzy C-Means Clustering, Generalized Shape Theory & Metric, Nanomaterial, Nanoimaging, Process Capability Index.