Optimization of cutting inserts geometry using DEFORM-3D: Numerical simulation and experimental validation

Nowadays, the accuracy of machining parts is essential in order to compete in a global market as demanding as machining. Due to the high cost of these machines continuous operation is required, with a reduction of the downtime owing to production readiness, maintenance or breakdowns. Among all the sources of error that affect the accuracy of machining parts, this paper is focused on improving the positioning accuracy of the machine. This requires periodic inspection of the machine tool, which should be included in maintenance operations.Volumetric verification is a novel technique that is being progressively introduced in machine tool maintenance operations, significantly reducing the time required. Unlike other techniques, this is based on non-linear mathematical models and the optimization process increases the influence factors. This modelling provides a re-creation of the whole verification process for all the influence factors; this allows the determination of the best measurement system distribution and the identification of techniques to use to characterize geometric errors. Thus, the verification time required is reduced, unnecessary tests are eliminated, the conditions under which real tests should be carried out are obtained in advance and machine tool accuracy is improved.

Section: Introductionmentioning

confidence: 99%

Modelling of Computer-Assisted Machine Tool Volumetric Verification Process

Aguado¹,

Velázquez²,

Samper³

2016

“…Surface quality, respectively surface roughness, has an important influence on technological time and costs, i. e. productivity [8]. On this basis, many scientificresearch projects and scientific papers of experimental investigations which are largely based on previously conducted and planned experiments aim at optimizing cutting parameters, modelling and predicting surface roughness to obtain a desired level of surface quality of machined products [9]. In this sense, many statistical (regression) models and models based on the application of artificial intelligence models have been developed.…”

Section: Introductionmentioning

confidence: 99%

Modelling and Simulation of Surface Roughness in Face Milling

Šimunović¹,

Šimunović²,

Šarić³

2013

The paper presents a research on machined surface roughness in face milling of aluminium alloy on a low power cutting machine. Based on the results of the central-composite plan of experiment with varying machining parameters (number of revolutions -spindle speed n, feed rate f and depth of cut a) and the roughness observed as output variable, two models have been developed: a regression model and a model based on the application of neural networks (NN model). The regression model (coefficient of determination of 0.965 or 0.952 adjusted) with insignificant lack of fit, provides a very good fit and can be used to predict roughness throughout the region of experimentation. Likewise, the model based on the application of neural networks approximates well the experimental results with the level of RMS (Root Mean Square) error in the phase of validation of 4.01 %.

“…A finite element model of the milling process was designed to determine the residual stress distribution across the depth of the machined surface. Tamizharasan and Senthil Kumar [14] attempted to minimize flank wear of uncoated carbide inserts by finite element modelling and simulation. The effect of tool geometries on performance measures of flank wear, surface roughness and cutting forces generated were evaluated.…”

Section: Introductionmentioning

confidence: 99%

Finite Element Modelling and Simulation of Chip Breaking with Grooved Tool

Deng¹,

Zi²,

Li³

et al. 2013

A finite element model is presented to simulate chip breaking when orthogonal turning medium carbon steel with a grooved cutting tool is used. The chip formation, chip breaking, cutting force, stress, strain and temperature are simulated by the thermo-elastic-plastic finite element method, using commercial finite element software. The cutting process is simulated from the initial to the steady-state of cutting force, and then to periodic fractures of machined chip, by incrementally advancing the cutting tool. Normalized Cockcroft & Latham's criterion is employed to predict the effect of tensile stress on chip fracture. The cutting force and bending moment are analysed to explain the mechanism of chip breaking. Experiments on the application of the grooved cutting tool were performed. The simulated broken chip profile and cutting force compare well with experimental observations that the established FE model is capable of capturing the overall trend of the experimental results.