A neural network-based model for the prediction of cutting force in milling process. A progress study on a real case

Abstract

In spite of recent developments focused on milling process optimization through an effective cutting force control, there is need of analysis the transient response of these systems because undesirable oscillations in cutting force could be harmful to the quality of finishing surface and tool. The main goal of this work is to develop a versatile neural network model so that by its on-line running one can predict mean cutting force under commonly encountered conditions. Using this model, easily obtained from straightfonvard machining test, further developments of complex adaptive controllers and monitoring systems can be carried out. As a result a good model for predicting the cutting process has been obtained.

Optimization of CNC ball end milling: a neural network-based model

“…Tansel et al [4] developed a cutting force variation estimator (CFVE) based on artificial neural network, where the objective was to predict the cutting force variation in micro-machining applications. Alique et al [5] used a MLP model with a single hidden layer to predict the mean cutting force based on the axial depth of cut and feet rate. The authors demonstrated the ability of ANN to precisely model the milling process, while maintaining simple topologies.…”

“…[5,7]). This training time was obtained utilizing a Windows NT PC with a Pentium ® II processor and 224 MB of memory.…”

Cutting force simplification model for output power smoothing and its simulation verification

“…When the simplification model is used for data fitting, too small a data feature set will make the model overly simplistic, which is called under fitting in machine learning [6]. To avoid under fitting and ensure the data for the fit be the greatest degree of characterization of the entire cutting process as well as the accuracy of the calculations, the data points for the fitting provide as follows: 1) Taking the cut-in angle of No.…”

“…A case study is carried out on the flat end mill tool: tooth number 2, diameter 15mm, 25 degree helix angle and the work piece material grade 45 quenched and tempered steel 28-32HRC, and a part of the calculation results are shown as the following: (6) As the fitting degree is an important measurement index in the parameter fitting, it is necessary to carry on the F test to the fitting formula and its parameters. The test model is constructed as…”

Hybrid Incremental Model for Imbalance Detection in Ultra-high Precision Rotating Devices

“…Applications of artificial neural networks are of particular interest because of their ability to accurately model any nonlinear function and their excellent learning capacity [5,6]. Also, fuzzy systems have become a consolidated technology in the last few decades, although there are still some challenges to be resolved [7].…”