...” ( SEM ) and “artificial neural network” ( ANN ) was used. Data were collected through a structured questionnaire from the Indian manufacturing SMEs. SEM validated hypothesised relationships, and ANN identified and ranked the most influential factors. Findings The outcomes show...

... more energy during deformation, maintaining their shape integrity. An artificial neural network ( ANN ) was trained to reveal the relationships between the design parameters and mechanical properties. Findings According to SHAP values, the highest significance in the ANN model was determined...

... (ASTM) D638’s Types I and II test standards. Design/methodology/approach The prediction approach combines artificial neural network (ANN) and finite element analysis (FEA), Monte Carlo simulation (MCS) and experimental testing for estimating tensile behavior for FDM considering uncertainties...

..., with experiments designed using central composite design (CCD). The impact of process parameters, including media viscosity, extrusion pressure, layer thickness and finishing time, on percentage improvement in surface roughness (%ΔRa) and material removal rate were analysed. Artificial neural network (ANN...