This research work aims to optimize double pipe heat exchanger performance using Taguchi, ANOVA, and ANN. Experimental trials involved varying ferric oxide nanoparticles, cut radius, and volume-based flow rate. Twisted tapes with ratios of 3, 5, and 7 were placed within the tube. Assessed heat transfer characteristics included h, Nu, ff, and thermal performance factor. Taguchi, ANOVA, and ANN optimization techniques were applied to the experimental data. A Taguchi optimization using an L9 orthogonal array focused on input attributes (Vol % of nanoparticles, flow rate, radius of cut), with output attributes being heat transfer co-efficient (h), Nusselt number (Nu), friction factor(ff) and thermal performance factor. Results revealed a notable flow rate effect on enhancing h, Nu, and ff, while the addition of nanoparticles significantly influenced thermal performance. Taguchi and ANOVA were conducted using MINI Tab and ANN was implemented through MATLAB. Test data demonstrated that nanoparticle dispersants in nanofluid significantly improved heat transfer properties, consistent with the noteworthy improvement indicated by optimization techniques. The convective heat transfer coefficient parameter showed improvement with a coolant flow rate of 50.29% and a volume of nanoparticles at 27.32%. The enhancement of Nusselt number (Nu) was influenced by a coolant flow rate of 50.34% and a volume percent of nanoparticles at 34.25%. The thermal performance factor was significantly influenced by the volume percent of nanoparticles (79.75%) and the radius of cut (3.83%).The experimental data aligned well with findings from Taguchi and ANN.