In the aviation industry, automated inspection is essential for ensuring quality of production. It allows acceleration of procedures for quality control of parts or mechanical assemblies. As a result, the demand of intelligent visual inspection systems aimed at ensuring high quality in production lines is increasing. In this work, we address a very common problem in quality control. The problem is verification of presence of the correct part and verification of its position. We address the problem in two parts: first, automatic selection of informative viewpoints before the inspection process is started (offline preparation of the inspection) and, second, automatic treatment of the acquired images from said viewpoints by matching them with information in 3D CAD models is launched. We apply this inspection system for detecting defects on aeronautical mechanical assemblies with the aim of checking whether all the subparts are present and correctly mounted. The system can be used during manufacturing or maintenance operations. The accuracy of the system is evaluated on two kinds of platform. One is an autonomous navigation robot, and the other one is a handheld tablet. The experimental results show that our proposed approach is accurate and promising for industrial applications with possibility for real-time inspection.