Authors: Navin N. Acharya, Dennis K.J. Lin
Addresses: Harold and Inge Marcus Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, 310 Leonhard Building, University Park, PA 16802, USA. ' Supply Chain and Information Systems, The Pennsylvania State University, 483 Business Building, University Park, PA 16802, USA
Abstract: Nanomanufacturing promises to increase quality, productivity and efficiency of existing technologies and has the potential to accelerate commercialisation of products and benefit various industries. As this technology is still in its discovery stage, there is a tremendous amount of experimentation occurring every day. Often in a nanomanufacturing setup, a large number of factors can be listed as possible sources of effects and among those, only a few are actually significant. A problem frequently encountered in nanomanufacturing is how to reduce the total number of experiments while estimating a large number of effects. Realising this challenge and the growing application of statistical techniques to discover relationships at the nanoscale, we advocate the use of supersaturated designs to nanomanufacturing settings. Here, we develop a supersaturated design, which is effective in identifying significant effects with minimal experimental runs for a process for the fabrication of ZnO nanorods, and discuss the analysis techniques.
Keywords: design of experiments; DOE; nanomanufacturing scaling-up; screening experiment; supersaturated design; variable selection; ZnO nanorods; nanotechnology; zinc oxide; nanorod fabrication.
International Journal of Nanomanufacturing, 2008 Vol.2 No.4, pp.319 - 330
Published online: 15 Jan 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article