A study on the performance of various predictive models based on artificial neural network for backward metal flow forming process

P Banerjee, R Laha, MK Dikshit, NB Hui… - International Journal on …, 2024 - Springer
Backward metal flow forming is an incremental forming process that is used to manufacture
near shape products with precise dimensions. Among the most important application fields …

Experimental study and analysis of surface roughness of the flow formed H30 alloy tubes

TN De, B Podder, NB Hui, C Mondal - Materials Today: Proceedings, 2021 - Elsevier
Surface roughness is one of the most important parameters of a finished, high precision axi-
symmetric product manufactured by the flow forming technology. Consequently, the …

Modelling and optimization of mean thickness of backward flow formed tubes using regression analysis, particle swarm optimization and neural network

P Banerjee, NB Hui, MK Dikshit, R Laha, S Das - SN Applied Sciences, 2020 - Springer
In this study, the relationship between the input process parameters and the output
parameters of the backward metal flow forming process is established using a full factorial …

Experimental estimation and numerical optimization of 'cylindricity'error in flow forming of H30 aluminium alloy tubes

TN De, B Podder, NB Hui, C Mondal - SN Applied Sciences, 2021 - Springer
The present article analyses the influence of flow forming input parameters on the
development of “cylindricity error” in H30 aluminum alloy seamless tubes fabricated by a …

Data-Driven Evaluation of Predictive Models for Estimation of Springback in Backward Metal Flow Forming Process

D Kachroo, P Banerjee, A Bera, NB Hui - International Conference on …, 2024 - Springer
Springback is common defect when soft materials are formed during backward metal flow
forming process. Springback is a combinational effect of roller geometry, process …

Models for Estimation of Springback in Backward Metal Flow Forming

D Kachroo, P Banerjee, A Bera… - … : Select Proceedings of …, 2024 - books.google.com
The backward metal flow forming process finds extensive application in the auto-motive,
defence, and aerospace industries [1, 2]. Flow forming is a near-net-shape advanced …

[PDF][PDF] Application of Adaptive Neuro-Fuzzy Inference System for Prediction of Mean Thickness in Backward Metal Flow Forming Process

P Banerjee, A Karmakar, N Hui - Acta Mechanica Slovaca, 2021 - researchgate.net
In the backward metal flow forming process, the mean thickness of flow formed tubes is
crucial in determining the quality. Consequently, predicting the mean thickness in …

[PDF][PDF] FE MODELLING OF THREE DIMENSIONAL STAGGERED BACKWARD METAL FLOW FORMING PROCESS.

P Banerjee, NB Hui, MK Dikshit… - International Journal of …, 2021 - researchgate.net
A three-dimensional Finite Element (FE) model for a backward flow forming process is
developed using ABAQUS simulation software. Forming parameters such as feed speed …