Design of Experiments: A Key to Innovation in Nanotechnology

Abstract

At the nanoscale, there are often very complex relationships among input design parameters and process or product outputs. It would be prohibitively time consuming to perform all of the combinatorially possible experiments in order to comprehend these relationships. However, statistical design of experiments (DoE) is a technique that can be used to efficiently explore the relationships and develop greater understanding. Consequently, DoE is becoming increasingly central to the advancement of nanotechnology and nanomanufacturing. In this chapter, we begin with an introduction to DoE in Section 8.1. In Section 8.2, we discuss the One Factor At A Time approach which is generally used among scientists and engineers. In Section 8.3, we consider traditional methods implemented in nanotechnology experimentation in practice. Next, in Section 8.4, we propose modern DoE methods that are appropriate for nanotechnology and nanomanufacturing. Section 8.5 provides a table of suggested DoE methods that map to particular areas within nanotechnology as well as a table of all of the articles in nanotechnology that we reviewed for this chapter that use statistical experimentation. Finally, conclusions and final remarks are given in Section 8.6. © 2010 Elsevier Inc. All rights reserved.