Accuracy and Fitting-Time Minimization in the Reverse Engineering of Prismatic Features

Abstract

Abstract In many years of industry, it is desirable to create geometric models of existing objects for which no such models are available. Reverse engineering transforms real parts into engineering models and concepts. This paper presents an approach for fitting three-dimensional prismatic features using real-coded genetic algorithms. The approach is compared with the Nelder Meade Simplex search method as a variant of the traditional direct search method. The results show the superiority of the real-coded genetic algorithms over the traditional direct search method with respect to accuracy. The paper also concerns with the minimization of the fitting time through minimizing the number of objective function evaluations. This is done by optimizing the genetic algorithms parameters such as the number of times for which the various cross-overs and mutations should be applied.