Research on the relationship between workpiece surface machining quality and turning tool wear

With excellent properties, high-temperature superalloys have become the main application materials for aircraft engines, gas turbines, and many other devices. However, superalloys are typically difficult to machine, especially for the thread cutting. In this article, an ultrasonic vibration–assisted turning system is proposed for thread cutting operations in superalloys. A theoretical analysis of ultrasonic vibration–assisted thread cutting is carried out. An ultrasonic vibration–assisted system was integrated into a standard lathe to demonstrate thread turning in Inconel 718 superalloy. The influence of ultrasonic vibration–assisted machining on workpiece surface quality, chip shape, and tool wear was analyzed. The relationship between machining parameters and ultrasonic vibration–assisted processing performance was also explored. By analyzing the motion relationship between tool path and workpiece surface, the reasons for improved workpiece surface quality by ultrasonic vibration–assisted machining were explained.

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Analysis of influencing factors for the dressing process in double side face grinding

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-020-06507-z ◽

2021 ◽

Author(s):

Eckart Uhlmann ◽

Linus Lichtschlag

Keyword(s):

Grain Size ◽

Tool Wear ◽

Influencing Factors ◽

Scientific Data ◽

Speed Ratio ◽

Workpiece Surface ◽

Principal Influence ◽

Side Face ◽

Face Grinding ◽

Wear Condition

AbstractIn grinding, the design of the dressing process is an essential part of work preparation and restoration of the grinding wheel’s profile and cutting ability. In contrast to most grinding processes, the choice of dressing parameters in double face grinding with planetary kinematics has so far only been experience-based. As a consequence, the dressing process causes a higher degree of tool wear than the machining of the workpieces. A focused design of the dressing process based on a scientific data could help to improve the ecological and the economic efficiency by reducing tool wear and the amount of dressing tools used. In this paper, methods for determining the wear condition and the result of the dressing process, including macro- and microscopic characteristic are presented. This includes a correlation analysis between parameters of wear characteristics and workpiece surface quality. Furthermore, technological investigations are carried out in order to systematically limit the main influencing factors on the dressing process. As a result, the parameters dresser grain size dgd, rotational speed ratio nld and the machined dresser height ∆hd are identified as significant for dressing. The knowledge about their principal influence on the dressing result could provide the basis for further research.

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Diamond tool wear monitoring by sensory analysis in milling of absolute black granite

Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture ◽

10.1177/09544054211040642 ◽

2021 ◽

pp. 095440542110406

Author(s):

Sandro Turchetta ◽

Luca Sorrentino ◽

Gianluca Parodo

Keyword(s):

Tool Wear ◽

Cutting Tools ◽

Depth Of Cut ◽

Surface Machining ◽

Diamond Tools ◽

The Matrix ◽

Cutting Force Components ◽

Force Components ◽

Natural Stones ◽

And Performance

Diamond tools suitable for machining operations of natural stones can be divided into two groups: cutting tools, including blades, the circular blades and the wires, and the surface machining ones, involving mills and grinders, that can be of different shapes. For the stone sawing process, the most adopted tool type is the diamond mill, whose duration and performance are influenced by various elements such as: the mineralogical characteristics of the material to be machined; the working conditions such as the depth of cut, the feed rate and the spindle speed; the production process of the diamond segment and the characteristics of both the matrix and the diamond, such as the size, the type and the concentration of the diamonds and the metal bond formulation hardness. This work allows to indirectly assess the wear of sintered diamond tools by signal analysis (in time and frequency domain) of the cutting force components acquired in the process. The results obtained represent a fundamental step for the development of a sensory supervision system capable of assessing the tool wear and hence to modify the process parameters in process, in order to optimize cutting performance and tool life.

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Cutting Performance of Different Coated Micro End Mills in Machining of Ti-6Al-4V

Micromachines ◽

10.3390/mi9110568 ◽

2018 ◽

Vol 9 (11) ◽

pp. 568 ◽

Cited By ~ 5

Author(s):

Zhiqiang Liang ◽

Peng Gao ◽

Xibin Wang ◽

Shidi Li ◽

Tianfeng Zhou ◽

...

Keyword(s):

Tool Wear ◽

Cutting Edge ◽

Micro Milling ◽

End Mill ◽

Coating Materials ◽

Edge Chipping ◽

Workpiece Surface ◽

Micro End Mill ◽

End Mills ◽

Flank Surface

Tool wear is a significant issue for the application of micro end mills. This can be significantly improved by coating materials on tool surfaces. This paper investigates the effects of different coating materials on tool wear in the micro milling of Ti-6Al-4V. A series of cutting experiments were conducted. The tool wear and workpiece surface morphology were investigated by analyzing the wear of the end flank surface and the total cutting edge. It was found that, without coating, serious tool wear and breakage occurred easily during milling. However, AlTiN-based and AlCrN-based coatings could highly reduce cutting edge chipping and flank wear. Specifically, The AlCrN-based coated mill presented less fracture resistance. For TiN coated micro end mill, only slight cutting edge chipping occurred. Compared with other types of tools, the AlTiN-based coated micro end mill could maximize tool life, bringing about an integrated cutting edges with the smallest surface roughness. In short, the AlTiN-based coating material is recommended for the micro end mill in the machining of Ti-6Al-4V.

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Study of the Relationship between Tool Wear and Surface Finish in Turning with Carbide Tool

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.902.95 ◽

2014 ◽

Vol 902 ◽

pp. 95-100 ◽

Cited By ~ 2

Author(s):

Heraldo J. Amorim ◽

Augusto O. Kunrath Neto

Keyword(s):

Surface Roughness ◽

Tool Wear ◽

Surface Finish ◽

Cutting Speed ◽

Single Equation ◽

Carbon Steels ◽

High Dispersion ◽

Exponential Relationship ◽

Processed Material ◽

The Relationship

The aim of this work is to analyze the tool wear effects on surface finish of machined components. Long-term machinability tests were performed for ASTM 1040 and 1045 carbon steels with carbide tools, in which tool wear and surface roughness were periodically evaluated. Surface finish was analyzed as a function of processed material and cutting speed with new machining tool, and a significant influence was found for cutting speed at a confidence interval of 10%. When evaluated as a function of time and tool wear, surface roughness showed an exponential relationship with both variables. However, a high dispersion occurs close to the end of tool life, especially for AISI 1040 steel. Weak influence of cutting speed (for the range of speeds tested) was observed on the relationship between tool wear and surface finish, indicating that a single equation can describe its behavior for all studied conditions. The relationship between the surface roughness and the cutting time was found to be stronger for the ABNT 1040 steel.

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Intelligence Selection System for Honing Parameter Based on Genetics and Artificial Neural Networks

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.102-104.846 ◽

2010 ◽

Vol 102-104 ◽

pp. 846-850

Author(s):

Wen Yu Pu ◽

Yan Nian Rui ◽

Lian Sheng Zhao ◽

Chun Yan Zhang

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Selection System ◽

Process Data ◽

Replacement Strategy ◽

Machining Quality ◽

Main Factors ◽

Artificial Neural ◽

Neural Networks Optimization ◽

The Relationship

Appropriate selecting of process parameters influences the machining quality greatly. For honing, the main factors are product precision, material components and productivity. In view of this situation, a intelligence selection model for honing parameter based on genetics and artificial neural networks was built by using excellent robustness, fault-tolerance of artificial neural networks optimization process and excellent self-optimum of genetic algorithm. It can simulate the decision making progress of experienced operators, abstract the relationship from process data and machining incidence, realize the purpose of intelligence selection honing parameter through copying, exchanging, aberrance, replacement strategy and neural networks training. Besides, experiment was performed and the results helped optimize the theories model. Both the theory and experiment show the updated level and feasibility of this system.

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Generalized Mechanistic Force System Model of Ball-End Milling for Sculpture Surface Machining

10.1115/imece2001/med-23303 ◽

2001 ◽

Author(s):

Ismail Lazoglu

Keyword(s):

End Milling ◽

Mechanistic Model ◽

Milling Process ◽

Force System ◽

Workpiece Surface ◽

Surface Machining ◽

Ball End Milling ◽

End Milling Process ◽

Validation Experiments ◽

Good Agreement

Abstract In this paper, a new mechanistic model is developed for the prediction of cutting force system in ball-end milling process. The key feature of the model includes the ability to calculate the workpiece / cutter intersection domain automatically for a given cutter location (CL) file, cutter and workpiece geometries. Moreover, an analytical approach is used to determine the instantaneous chip load and cutting forces. The model also employs a Boolean approach for given cutter, workpiece geometries, and the CL file in order to determine the surface topography and scallop height variations along the workpiece surface which can be visualized in 3-D. Some of the typical results from the model validation experiments performed on Ti-6A1-4V are also reported in the paper. Comparisons of the predicted and measured forces as well as the surface topographies show good agreement.

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Tool Wear Prediction in Single-Sided Lapping Process

Machines ◽

10.3390/machines8040059 ◽

2020 ◽

Vol 8 (4) ◽

pp. 59

Author(s):

Norbert Piotrowski

Keyword(s):

Quality Control ◽

Tool Wear ◽

Product Quality ◽

Computer Model ◽

Rotational Speed ◽

Data Driven ◽

Product Quality Control ◽

Abrasive Grains ◽

Tool Wear Prediction ◽

The Relationship

Single-sided lapping is one of the most effective planarization technologies. The process has relatively complex kinematics and it is determined by a number of inputs parameters. It has been noted that prediction of the tool wear during the process is critical for product quality control. To determine the profile wear of the lapping plate, a computer model which simulates abrasive grains trajectories was developed in MATLAB. Moreover, a data-driven technique was investigated to indicate the relationship between the tool wear uniformity and lapping parameters such as the position of conditioning rings and rotational speed of the lapping plate and conditioning rings.

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