Dimensional analysis for investment selection in industrial robots

Abstract

Investment evaluation and selection of industrial robots is a complex multi-criteria decision-making task. This paper considers the possibility of applying to the robot selection problem a known mathematical method based on Dimensional Analysis (DA) theory. It is shown how it is possible to obtain an easy, efficient and robust decision-making support system which overcomes all attribute dimension problems. In particular, the robustness of the DA approach when compared with judgements made by a group of experts concerning different factors and weights, is evaluated. DA low sensitivity is compared with a Weighted-point decision method found in the literature.