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Abstract. The use of composites made of polyamide 6.6 matrix and short-glass-fibers in automobile industry is progressive due to its low density and cost. The injection molded short glass fiber-reinforced (SGFR) thermoplastics structural parts such as intake, manifold and engine mount housing, induce complex fiber orientation distributions (FOD). This microstructure governs the macroscopic properties such as the mechanical stiffness and fatigue resistance. To estimate the FOD on such industrial parts at complex angles and ribs, we rely on simulation results and micro tomography analysis. The interest of this paper is to develop a semi-automated, quick and efficient orientation tensor identification approach from 2D microscopic images, which is capable of observing relatively larger surface compared to micro tomography. We finally conclude by comparing it with micro tomography and simulation results. Furthermore, we investigate its relevance with fatigue service ability.