Dimensional Control in a Shipbuilding Workshop Based on High-Density Point Clouds Using High Performance Computing

Abstract

In many industries, the quality control process of manufactured products has become one of the most fundamental tasks to minimize manufacturing problems and production costs. High density point clouds are often mandatory to obtain a reliable representation of the products inspected. In this work, we present a parallelization on the Key Point Characteristic extraction of a ship panel, used for the quality control process, on a shared memory system using OpenMP. Experimental results show accelerations of up to 4,1x.