Archives > Volume 15 | Number 1 | March 2020 > pp 5–17
Advances in Production Engineering & Management
Volume 15 | Number 1 | March 2020 | pp 5–17
Neuro-mechanistic model for cutting force prediction in helical end milling of metal materials layered in multiple directions
Zuperl, U.; Cus, F.; Zawada-Tomkiewicz, A.; Stępień, K.
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A B S T R A C T
In machining of multi-layer metal materials used frequently for the manufacture of transfer sheet-metal forming tools, the cutting edge is often damaged because of cutting force peaks. Therefore, a neuro-mechanistic model, presented in this paper, has been created for accurate prediction of cutting forces in helical end milling of multidirectional layered materials. The generalized model created takes into account the complex geometry of the helical end milling cutter, the instantaneous chip thickness and the direction of depositing of the individual layer of the multidirectional layered material considered in the calculation through predicted specific cutting forces. For the prediction of specific cutting forces for individual layers a neural network is incorporated in the model. The comparison with experimental data shows that the model predicts accurately the flow of cutting force in milling of multidirectional layered metal materials for any combination of cutting parameters, tool engagement angle and directions of depositing three layers of material. The predicted cutting force values agree well with the values obtained, the maximum error of predicted cutting forces is 16.1 % for all comparison tests performed.
A R T I C L E I N F O
Keywords • Helical end milling; Multidirectional layered metal material; Cutting forces; Specific cutting forces; Neuro-mechanistic model; Modelling; Prediction; Artificial neural networks
Corresponding author • Zuperl, U.
Article history • Received 18 April 2019, Revised 16 March 2020, Accepted 23 March 2020
Published on-line • 31 March 2020
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