Prediction of average surface roughness and formability in single point incremental forming using artificial neural network

• Autorzy: Mulay Amrut , Ben B. Satish , Ismail Syed , Kocanda Andrzej

Identyfikatory

DOI

10.1016/j.acme.2019.06.004

• Języki publikacji: EN

Abstrakty

EN

Single point incremental forming (SPIF) is a flexible, innovative, and cheap process for rapidmanufacturing of complex sheet metal parts. It is a crucial task for engineers to predict aprocess when many independent parameters are affecting simultaneously its performance.An artificial neural network (ANN) based prediction model was developed to evaluateaverage surface roughness (Ra) and maximum forming angle (Ømax) while SPIF forming ofAA5052-H32 material. A feedforward backpropagation network with Levenberg–Marquardtalgorithm was employed to build ANN model. The ANNs (4-n-1, 4-n-2) were generated byintroducing different combinations of transfer functions and a number of neurons. Theconfirmation runs were performed to verify the agreement between the ANN predicted andthe experimental results. The developed ANN model (4-n-1) was capable of predicting theprocess response with an excellent accuracy and resulted in overall R-value, MSE, and MAPEof 0.99807, 0.0209, and 5.96% for Ra0.99913, 0.0281, and 0.003 for Ømax. The optimum 4-n-2model was built with overall R-value, MSE of 0.99999 and 0.057194, respectively. Hence, itwas found that the engineering efforts may be reduced in the SPIF process with successfulANN model implementation.

Słowa kluczowe

EN

surface roughness; formability; artificial neural network; incremental forming; measurement

PL

chropowatość powierzchni; formowalność; sztuczna sieć neuronowa; pomiary; formowanie przyrostowe

• Wydawca: Springer ; Wrocław University of Science and Technology
• Czasopismo: Archives of Civil and Mechanical Engineering
• Rocznik: 2019
• Tom: Vol. 19, no. 4
• Strony: 1135--1149
• Opis fizyczny: Bibliogr. 40 poz., rys., tab., wykr.

Twórcy

autor

Mulay Amrut

• Mechanical Engineering Department, Indian Institute of Technology, Bombay 400076, India

autor

Ben B. Satish

• Mechanical Engineering Department, National Institute of Technology, Warangal 506004, India

autor

Ismail Syed

• Mechanical Engineering Department, National Institute of Technology, Warangal 506004, India

autor

Kocanda Andrzej

• Faculty of Management and Computer Modeling, Kielce University of Technology, 25-314 Kielce, Poland

Bibliografia

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Uwagi

PL

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020)