Designing an Expert System to Predict the Mechanical Properties of Airframe of Unmanned Air Vehicle Fabricated by Fused Filament Fabrication Using Firefly Nature-Inspired Algorithm

The rapid advancement in unmanned aerial vehicles (UAVs) necessitates the development of lightweight and robust airframes to enhance performance and efficiency. The present work focuses on the design and implementation of an expert system to predict the mechanical properties of UAV airframes fabricated using fused filament fabrication (FFF), also known as fused deposition modeling (FDM), with a focus on carbon fiber-reinforced feedstock. The study employs the Firefly Algorithm (FA), a nature-inspired optimization technique, to optimize key FDM process parameters, that is, layer thickness, nozzle temperature, and part orientation. The response parameters evaluated are tensile strength, flexural strength, and weight measurement, which are critical for the structural integrity and performance of UAV airframes. Central composite design (CCD) and response surface methodology (RSM) are utilized to develop a predictive model, while analysis of variance (ANOVA) is employed to determine the significance of the process parameters on the mechanical properties. The integration of FA allows for efficient exploration and exploitation of the parameter space, leading to optimal settings that enhance the quality and performance of the fabricated parts. This study demonstrates that by leveraging the FA for parameter optimization, it is possible to achieve significant improvements in the mechanical properties of UAV airframes, resulting in lighter and stronger components. The developed expert system provides a robust framework for predicting and optimizing the mechanical properties of FDM-fabricated parts, facilitating the design and manufacturing of high-performance UAVs. The findings contribute to the broader application of advanced optimization algorithms in additive manufacturing and underscore the potential of carbon fiber-reinforced materials in UAV applications.-->