Concurrent design of a nanoactuator for “X-abilities” using the multiple-attribute decision-making approach

Abstract

Organizations are deploying well-designed nanoactuators supporting converged applications of defense, mechanical industry, biological applications, and so on. An attempt is made to integrate concurrent engineering and multiple-attribute decision-making approaches to design and develop nanoactuators for a number of abilities, for example, actuation, modelization, realization, and performance. Attributes corresponding to these abilities are identified using cause and effect diagram. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) that is suitable for optimum design of nanoactuators is selected. The method permits to consider concurrently all the attributes contributing to X-abilities. The method also permits to carry out sensitivity analysis of one or more attributes simultaneously and determine optimum values of parameters. The concurrent engineering and multiple-attribute decision-making method ensures that optimally selected nanoactuator elements are closest to the hypothetical best and farthest from the hypothetical worst solution in order to design nanoactuators for the application under consideration. Research methodology in the form of step-by-step procedure is implemented with the help of an illustrative example. An agenda has been set for further research using this methodology.