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In present study, artificial intelligence systems intertwine with mechanical systems for reducing the manufacturing time and cost of products. In Fused Deposition Modeling (FDM) optimum value of deposition angle significantly varies with product geometry; hence, prediction and validation is performed using ensemble based random forest machine learning model. The training data is generated using different shapes and geometries whereas correlation based feature selection technique is employed to explore the crucial features of products. T
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