Development and implementation of crater and flank tool wear model for hard turning simulations

Cappellini, Cristian; Abeni, Andrea

doi:10.1007/s00170-022-08885-y

Cited by 18 publications

(4 citation statements)

References 45 publications

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“…The flank wear value, accepted as a criterion for evaluating the cutting tool life, can provide information, especially about the material's machinability. According to the ISO 3685:1993 tool life test standard [49], for a tool to complete its life, it must reach an average flank wear value of 0.3 mm, a maximum flank wear value of 0.6 mm, or a severe tool failure criterion [40,50,51].…”

Section: Maximum Flank Wearmentioning

confidence: 99%

The Effect of Cellulose Nanocrystal-Based Nanofluid on Milling Performance: An Investigation of Dillimax 690T

Usca

2023

Polymers

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Machining high-strength structural steels often requires challenging processes. It is essential to improve the machinability of such materials, which are frequently needed in industrial manufacturing areas. Recently, it has become necessary to enhance the machinability of such materials using different nanopowders. In this study, different cooling/lubricating (C/L) liquids were prepared with cellulose nanocrystal (CNC) nanopowder. The aim was to improve the machinability properties of Dillimax 690T material with the prepared CNC-based cutting fluids. CNC nanopowders were added to 0.5% distilled water by volume, and a new nanofluid was produced. Unlike previous studies, base synthetic oil and CNC-based cutting fluid were sprayed on the cutting area with a double minimum quantity lubrication (MQL) system. Machinability tests were carried out by milling. Two different cutting speeds (Vc = 120–150 m/min), two different feed rates (f = 0.05–0.075 mm/tooth), and four different C/L environments (dry, MQL oil, CNC nanofluid, MQL oil + CNC nanofluid) were used in the experiments. In the study, where a total of 16 experiments were performed, cutting temperature (Tc), surface roughness (Ra), tool wear (Vb), and energy consumption results were analyzed in detail. According to the test results, significant improvements were achieved in the machinability properties of the material in the experiments carried out using CNC nanofluid. In particular, the hybrid C/L environment using MQL oil + CNC nanofluid improved all machinability metrics by over 15% compared to dry machining. In short, using CNC nanopowders offers a good milling process of Dillimax 690T material with effective lubrication and cooling ability.

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Section: Maximum Flank Wearmentioning

confidence: 99%

The Effect of Cellulose Nanocrystal-Based Nanofluid on Milling Performance: An Investigation of Dillimax 690T

Usca

2023

Polymers

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“…Therefore, the Finite Element Method (FEM) of machining processes has received much attention by numerous researchers in the last decades [3]. This method was successfully implemented to improve the understanding of crater and flank tool wear in turning [4] and determination of residual stresses [5] or interactions in the chip forming process with internal lubrication in sawing [6]. The underlying idea of FEM is the discretization of the tool and the workpiece and employing a stiffness structure [7].…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Approach for Cutting Force Prediction in FEM Machining Simulations Using Gradient Boosted Machines

Reeber,

Wolf,

Möhring

2024

JMMP

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Cutting simulations via the Finite Element Method (FEM) have recently gained more significance due to ever increasing computational performance and thus better resulting accuracy. However, these simulations are still time consuming and therefore cannot be deployed for an in situ evaluation of the machining processes in an industrial environment. This is due to the high non-linear nature of FEM simulations of machining processes, which require considerable computational resources. On the other hand, machine learning methods are known to capture complex non-linear behaviors. One of the most widely applied material models in cutting simulations is the Johnson–Cook material model, which has a great influence on the output of the cutting simulations and contributes to the non-linear behavior of the models, but its influence on cutting forces is sometimes difficult to assess beforehand. Therefore, this research aims to capture the highly non-linear behavior of the material model by using a dataset of multiple short-duration cutting simulations from Abaqus to learn the relationship of the Johnson–Cook material model parameters and the resulting cutting forces for a constant set of cutting conditions. The goal is to shorten the time to simulate cutting forces by encapsulating complex cutting conditions in dependence of material parameters in a single model. A total of five different models are trained and the performance is evaluated. The results show that Gradient Boosted Machines capture the influence of varying material model parameters the best and enable good predictions of cutting forces as well as deliver insights into the relevance of the material parameters for the cutting and thrust forces in orthogonal cutting.

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“…They found that turning speed has the main impact on tool wear, and turning depth has the least impact on tool wear. Cappellini C et al [8] and Suresh R et al [9] conducted a study on tool life prediction in hard turning.…”

Section: Introductionmentioning

confidence: 99%

Analysis of tool wear and morphology and residual stress of machined surface in hard turning

Zhou,

Wang,

Zou

et al. 2023

Ninth International Conference on Mechanical Engineering, Materials, and Automation Technology (MMEAT 2023)

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The precision machining technology of hard turning has always been concerned by scientific research institutions and manufacturing industries. Based on the single factor experiment, the wear of CBN tool, morphology of machined surface, residual stress during hard turning of W6Mo5Cr4V2 are analyzed by scanning electron microscope, ultra depth of field microscope, laser confocal electron microscope and X-ray residual stress instrument. The research results indicate that: (1) Adhesion, oxidation and friction in hard turning are the main causes of tool wear, the most significant turning parameter that affects the wear of CBN tool is turning speed. (2) High machining velocity, small feed and small cutting depth can obtain good machined surface quality. (3) The axial and tangential residual stresses produced by hard turning are mainly compressive stresses. When the turning depth is approximately 0.19mm, the tangential residual compressive stress is transformed into tensile stress.

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Development and implementation of crater and flank tool wear model for hard turning simulations

Cited by 18 publications

References 45 publications

The Effect of Cellulose Nanocrystal-Based Nanofluid on Milling Performance: An Investigation of Dillimax 690T

The Effect of Cellulose Nanocrystal-Based Nanofluid on Milling Performance: An Investigation of Dillimax 690T

A Data-Driven Approach for Cutting Force Prediction in FEM Machining Simulations Using Gradient Boosted Machines

Analysis of tool wear and morphology and residual stress of machined surface in hard turning

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