Nowadays, optimization of manufacturing and assembly operations requires taking into account the inherent processes variations. Geometric and dimensional metrology of mechanical parts is very crucial for the aerospace industry and contributes greatly to its. In a free-state condition, non-rigid parts (or compliant parts) may have a significant different shape than their nominal geometry (CAD model) due to gravity loads and residual stress. Typically, the quality control of such parts requires a special approach where expensive and specialized fixtures are needed to constrain dedicated and follow the component during the inspection. Inspecting these parts without jig will have significant economic impacts for aerospace industries, reducing delays and the cost of product quality inspection. The Iterative Displacement Inspection (IDI) algorithm has been developed to deal with this problem. In this paper, we propose a statistical approach based on the extreme value analysis to improve the identification module of the IDI. We tested our robust IDI algorithm on a simulated aerospace sheet metal part. The experiments show that the proposed approach is more robust and effective and extends the original IDI identification module in its methodology and applications.