Efficient 3D Alignment of Physical Structures with CAD Model Nominals in Manufacturing: A Genetic Algorithm Approach

In modern industry, the accurate alignment of components and machines in three-dimensional space is a major challenge, especially in fields such as automotive and aerospace. This work addresses the critical issue of aligning physical structures with their corresponding CAD models, a crucial step in ensuring accurate assembly and manufacturing processes. A novel alignment method is presented using genetic algorithms to optimize the six degrees of freedom of the measured coordinate system. This optimization minimizes the need for subsequent manual adjustments, increasing efficiency and accuracy. The method is applied to a practical case involving the assembly of sheet metal parts for truck cabins, using FARO tracker technology for measurements and MATLAB for analysis. The results of applying the genetic algorithm show a remarkable reduction in the number of fixture support elements to be adjusted from 16 to only 1, highlighting the effectiveness of this approach in streamlining the alignment process and improving overall manufacturing productivity.