Tool wear analysis in milling of locomotives wheels

AbstractThe present work aims to evaluate the tool wear during the milling process of locomotives wheels—class C. A digital microscope is used to identify both the wear and the damage. The wear or damage, when propagated, can compromise the wheel roughness, which has a significant economic importance to railroad maintenance. A system for image capture composed of an ISM-PM200S INSIZE Digital Microscope and the ISM-Pro software is used to measure the flank wear. Firstly, milling process is applied with different numbers of passes. The results showed that, after flank wear, the most common wear is the thermal crack. It is also possible to observe the appearance of chipping and fracture as a consequence of the combination of thermal and mechanical cracks in the same insert. The inserts are more damaged in the raceway, due to the hardening of this region during its use. Inserts in the frieze region also showed higher values of wear, justified by the conditions of the railway. The highest values observed are around 0.1 mm. It is possible to notice that some inserts showed other damages, such as breaks and chipping, even before reaching the end of life due to wear.

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The Analysis of Tool Wear in Milling CFRP with Different Diamond Coated Tool

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.667.231 ◽

2015 ◽

Vol 667 ◽

pp. 231-236 ◽

Cited By ~ 2

Author(s):

Xiao Fan Yang ◽

You Sheng Li ◽

Guo Hong Yan ◽

Ju Dong Liu ◽

Dong Min Yu

Keyword(s):

Tool Wear ◽

Flank Wear ◽

Milling Process ◽

Cutting Condition ◽

End Mill ◽

Reinforced Plastics ◽

Right Hand ◽

Coated Tool ◽

New Type ◽

Fiber Reinforced Plastics

Carbon fiber-reinforced plastics (CFRP) are typical difficult-to-machine materials, which is easy to produce many defects such as burrs, dilacerations, layering in milling process. And selecting the appropriate cutting tool has become the key to machining CFRP with high quality and efficiency. In the paper, the machining principle of milling CFRP with new type end mill was analyzed. The diamond coating of general right-hand end mill, cross-flute router and fine-cross-nick router were used to cutting CFRP under the same cutting condition. Through the comparative analysis of the workpiece’s surface quality and tool wear, it concluded that: compared with right-hand diamond coated end mill, cross-flute diamond coated router or fine-cross-nick diamond coated router could effectively suppress the appearance of burrs and dilacerations; abnormal coating peeling appeared in the flank face of right-hand diamond coated end mill, forming the boundary wear, which accelerated wear failure; the flank wear of diamond coated cross-flute router and fine-cross-nick router were both abrasive wear. Due to having more cutting edge than cross-flute router in cutting process, the flank wear of fine-cross-nick router was slower, and the tool life was longer. So it was more suitable for cutting CFRP.

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Software Development and Data Processing of Tool Wear Based on Mapping Measurement

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.383-390.4971 ◽

2011 ◽

Vol 383-390 ◽

pp. 4971-4976 ◽

Cited By ~ 1

Author(s):

Song Guo ◽

Chen Zhang ◽

Xi Hui Liu

Keyword(s):

Tool Wear ◽

Data Processing ◽

Measurement Method ◽

Flank Wear ◽

Great Influence ◽

Least Square Method ◽

Milling Process ◽

Processing Method ◽

Least Square ◽

Data Processing Method

In NC milling process, tool wear has great influence on the machining quality of product. In this paper, a mapping measurement method is used to obtain tool wear and a data processing method is proposed to deal with the data getting from the measurement. First, tool wear along radius of tool’s cross-section, which is called radial wear, can be obtained by mapping measurement method. Then tool flank wear can be easily calculated based on the established relationship between radial wear and flank wear. In order to get radial wear, we process those measured data that are obtained from mapping measurement. In this process, least square method is adopted to fit these data to get the radius of section circle at a certain position. So the radial wear can be obtained by comparing the radius of the fitting circle and the original radius of tool at a certain section. Finally, the data processing software is realized by using Visual C++ development tool according to the designed data processing method of tool wear.

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Using tool wear to increase process stability when milling Al7075 and AISI 4140+QT

Production Engineering ◽

10.1007/s11740-021-01059-x ◽

2021 ◽

Author(s):

Berend Denkena ◽

Alexander Krödel ◽

Andreas Relard

Keyword(s):

Tool Wear ◽

Flank Wear ◽

Load Capacity ◽

Milling Process ◽

Machining Process ◽

Depth Of Cut ◽

Process Stability ◽

Side Milling ◽

Machine Performance ◽

Cutting Processes

AbstractOne of the main limits of productivity during cutting processes is the occurrence of regenerative chatter. Due to these self-excited vibrations, the load capacity of the machine components, the tool as well as the machine performance cannot be fully utilized. There are several methods to stabilize the milling process. One is the use of increased process damping, which results from the contact of the tool’s flank face and the workpiece. The flank wear land naturally increases the contact between tool and workpiece. However, this effect has not been used to increase productivity in milling processes. This paper investigates with experiments and numerical simulations how tool wear affects process stability in milling of aluminum and steel. Therefore slot milling and side milling tests were carried out with tools of various states of flank wear. It could be shown that increasing flank wear allows to raise the depth of cut ap up to 300% in machining aluminum and perform the machining process with a higher productivity.

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Study on Tool Wear in Green Milling Ni-Based Superalloy

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1095.865 ◽

2015 ◽

Vol 1095 ◽

pp. 865-868

Author(s):

Hui Wang ◽

Yun Lu ◽

Jing Jing Liu

Keyword(s):

Water Vapor ◽

Tool Wear ◽

Flank Wear ◽

Milling Process ◽

Cutting Condition ◽

Carbide Tool ◽

Dry Cutting ◽

Machined Surface ◽

Machined Surface Roughness ◽

Ionized Air

In order to solve the difficult machining problem of Ni-based superalloy, the water vapor and ionized air was applied as coolant and lubricant in milling process. The tool wear experiments on water vapor, ionized air, wet and dry cutting with carbide tool YG6A machining Ni-based superalloy GH4169 was carried out. The result showed that tool wear was quickly on milling GH4169 with carbide tool YG6A, and increased with the cutting speed.The flank wear land was uneven and the boundary wear was serious. During the ionized air condition the flank wear was more slowly than wet and dry cutting condition, the values of flank wear were reduced about 15 and 10 percent respectively. In addition, the result showed that The milling force and machined surface roughness increased with the flank wear.

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The flank wear prediction in micro-milling Inconel 718

Industrial Lubrication and Tribology ◽

10.1108/ilt-01-2018-0031 ◽

2018 ◽

Vol 70 (8) ◽

pp. 1374-1380 ◽

Cited By ~ 2

Author(s):

Xiaohong Lu ◽

FuRui Wang ◽

Zhenyuan Jia ◽

Steven Y. Liang

Keyword(s):

Finite Element ◽

Tool Wear ◽

Cutting Forces ◽

Inconel 718 ◽

Flank Wear ◽

Milling Process ◽

Micro Milling ◽

Wear Prediction ◽

Content Type ◽

Micro Tool

Purpose Cutting tool wear is known to affect tool life, surface quality, cutting forces and production time. Micro-milling of difficult-to-cut materials like Inconel 718 leads to significant flank wear on the cutting tool. To ensure the respect of final part specifications and to study cutting forces and tool catastrophic failure, flank wear (VB) has to be controlled. This paper aims to achieve flank wear prediction during micro-milling process, which fills the void of the commercial finite element software. Design/methodology/approach Based on tool geometry structure and DEFORM finite element simulation, flank wear of the micro tool during micro-milling process is obtained. Finally, experiments of micro-milling Inconel 718 validate the accuracy of the proposed method for predicting flank wear of the micro tool during micro-milling Inconel 718. Findings A new prediction method for flank wear of the micro tool during micro-milling Inconel 718 based on the assumption that the wear volume can be assumed as a cone-shaped body is proposed. Compared with the existing experiment techniques for predicting tool wear during micro-milling process, the proposed method is simple to operate and is cost-effective. The existing finite element investigations on micro tool wear prediction mainly focus on micro tool axial wear depth, which affects size accuracy of machined workpiece seriously. Originality/value The research can provide significant knowledge on the usage of finite element method in predicting tool wear condition during micro-milling process. In addition, the method presented in this paper can provide support for studying the effect of tool flank wear on cutting forces during micro-milling process.

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Integrating object detection and image segmentation for detecting the tool wear area on stitched image

Scientific Reports ◽

10.1038/s41598-021-97610-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Wan-Ju Lin ◽

Jian-Wen Chen ◽

Jian-Ping Jhuang ◽

Meng-Shiun Tsai ◽

Che-Lun Hung ◽

...

Keyword(s):

Tool Wear ◽

Template Matching ◽

Cutting Tool ◽

Flank Wear ◽

End Milling ◽

Cutting Tools ◽

Milling Process ◽

Wear Area ◽

Learning Techniques ◽

The Times

AbstractFlank wear is the most common wear that happens in the end milling process. However, the process of detecting the flank wear is cumbersome. To achieve comprehensively automatic detecting the flank wear area of the spiral end milling cutter, this study proposed a novel flank wear detection method of combining the template matching and deep learning techniques to expand the curved surface images into panorama images, which is more available to detect the flank wear areas without choosing a specific position of cutting tool image. You Only Look Once v4 model was employed to automatically detect the range of cutting tips. Then, popular segmentation models, namely, U-Net, Segnet and Autoencoder were used to extract the areas of the tool flank wear. To evaluate the segmenting performance among these models, U-Net model obtained the best maximum dice coefficient score with 0.93. Moreover, the predicting wear areas of the U-Net model is presented in the trend figure, which can determine the times of the tool change depend on the curve of the tool wear. Overall, the experiments have shown that the proposed methods can effectively extract the tool wear regions of the spiral cutting tool. With the developed system, users can obtain detailed information about the cutting tool before being worn severely to change the cutting tools in advance.

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Correlative Flank Wear Analysis of Single Point Turning Inserts Using Acoustic Emission and Artificial Intelligence Techniques

Volume 7: Emerging Technologies; Recent Advances in Engineering ◽

10.1115/imece2008-67543 ◽

2008 ◽

Author(s):

R. Srinidhi ◽

Vishal Sharma ◽

M. Sukumar ◽

C. S. Venkatesha

Keyword(s):

Acoustic Emission ◽

Tool Wear ◽

Flank Wear ◽

Machining Process ◽

Work Piece ◽

Machining Parameters ◽

Wear Analysis ◽

Tools Wear ◽

Coated Carbide ◽

Ae Signals

Wear mechanism of a cutting tool is highly complex in that the processes of tool wear results from interacting effect of machining configurations. Various output generated by the study and analysis of each tool is extremely useful in analyzing the tool characteristics in general and to make efforts to obtain the estimated tool life in particular. The gradual process of tool wear has adverse influence on the quality of the surface generated and on the design specifications in the work piece dimensions and geometry, and causes, at the worst case, machine breakdown. Advanced manufacturing demands proper use of the right tool and emphasizes the need to check the wear rate. A scientific method of obtaining conditions for an optimal machining process with proper tools and control of machining parameters is essential in the present day manufacturing processes. Many problems that affect optimization are related to the diminished machine performance caused by worn out tools. One of the indirect methods of tool wear analysis and monitoring is based on the acoustic emission (AE) signals. The generation of the AE signals directly in the cutting zone makes them very sensitive to changes in the cutting process and provides a means of evaluating the wear of cutting tools. Wear parameters obtained in the process are analyzed with the output generated by using Multi Layer Perceptron (MLP) based back propagation technique and Adaptive Neuro Fuzzy Interference System (ANFIS). The results obtained from these methods are correlated for the actual and predicted wear. Experiments have been conducted on EN8 and, EN24 using Uncoated Carbide, Coated carbide and Ceramic inserts (Kennametal, India make) on a high speed lathe for the most appropriate cutting conditions. The AE signal analysis (considering signal parameters such as, ring down count (RDC), rise time (RTT), event duration (ED) and energy (EG). Flank wear in tools and corresponding cutting forces for each of the trials are measured and are correlated for various combinations of tools and materials of work piece.

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Influence of CAM Strategies on the Wear of Cutting Tools

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.834.90 ◽

2016 ◽

Vol 834 ◽

pp. 90-95

Author(s):

Rudolf Zaujec ◽

Peter Pokorný

Keyword(s):

Tool Wear ◽

High Speed ◽

Cutting Tool ◽

Cutting Tools ◽

High Speed Steel ◽

Milling Process ◽

Cnc Milling ◽

Cutting Tool Wear ◽

Digital Microscope ◽

Measuring Machine

This paper presents research on the influence of CAM strategies for wear and durability of milling tools. We used two machining principles in this process. In the first instance was constant point of contact with the tool and machining surface. The second method was changing point of the cutting edge in the milling process. Material of tool was hard alloy and high speed steel for machining steel 40CrMnMo7 and C45. The shape of cutting tool was a “Ball Nose” end mill. A DMU 85 monoBLOCK 5-axis CNC milling machine was used. The cutting tool wear was measured in Zoller Genius 3, universal measuring machine and digital microscope, Dino lite 2. The results show differences of cutting tool wear depending on the milling strategy and material of tool.

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