scholarly journals Vibration-based tool wear monitoring using Artificial Neural Networks fed by Spectral centroid indicator & RMS of CEEMDAN modes

2021 ◽  
Author(s):  
Mourad NOUIOUA ◽  
Mohamed Lamine BOUHALAIS
Keyword(s):  
Tool Wear ◽  
Tool Life ◽  
Laser Doppler Vibrometer ◽  
Machining Parameters ◽  
Machining Processes ◽  
Limit Value ◽  
Aisi 1045 Steel ◽  
Wear Monitoring ◽  
Artificial Neural ◽  
1045 Steel

Abstract In machining processes various phenomena occur during cutting operation. These phenomena can disturb the production through the reduction of part quality and accuracy. Therefore, a mastery of this cutting phenomena is needed to define the machining parameters and take full advantage of manufacturing process. An easy way to classify these phenomena is by monitoring incontrollable parameters, such as generated temperature and vibration. The acquired vibration signals can provide information regarding tool life, cutting performances and workpiece defects. This paper evaluates the possibility of monitoring the tool life during the turning process of AISI 1045 steel using Laser Doppler Vibrometer (LDV), the surface roughness has been measured along with the tool-wear until reaching its limit value of 300µm. Furthermore, this paper also outlines the application of CEEMDAN technique to process the acquired signals for the monitoring processes. RMS and SCI indicators have been used to describe the wear progress, then, the artificial neural network has been adopted to achieve a real time wear monitoring. The obtained results qualified the SCI indicator and ANN for online monitoring.

Tool tip cutting specific energy prediction model and the influence of machining parameters and tool wear in milling

2020 ◽  
Vol 234 (10) ◽  
pp. 1346-1354 ◽  
Author(s):  
Guoyong Zhao ◽  
Yu Su ◽  
Guangming Zheng ◽  
Yugang Zhao ◽  
Chunxiao Li
Keyword(s):  
Tool Wear ◽  
Prediction Model ◽  
Specific Energy ◽  
Machine Tools ◽  
Cutting Speed ◽  
Machining Parameters ◽  
Cutting Depth ◽  
Energy Prediction ◽  
Aisi 1045 Steel ◽  
1045 Steel

Most of the existing energy-consumption models of machine tools are related to specific machine components and hence cannot be applied to other machine tools with different specifications. In order to help operators optimize machining parameters for improving energy efficiency, the tool tip cutting specific energy prediction model based on machining parameters and tool wear in milling is developed, which is independent of the standby power of machine tools and the spindle no-load power. Then, the prediction accuracy of the proposed model is verified with dry milling AISI 1045 steel experiments. Finally, the influence of machining parameters and tool wear on tool tip cutting specific energy is studied. The developed model is independent of machine components, so it can reveal the influence of machining parameters and tool wear on tool tip cutting specific energy. The tool tip cutting specific energy reduces with the increase in the cutting depth, side cutting depth, feed rate, and cutting speed, while increases linearly as the tool wears gradually. The research results are helpful to formulate efficient and energy-saving processing schemes on various milling machines.

Tribology of Coated Tools in High-Speed Machining: A Tool Wear and “Equivalent Toolface” Geometry Based Study

2005 ◽  
Author(s):  
A. K. Balaji
Keyword(s):  
Tool Wear ◽  
High Speed ◽  
Tool Geometry ◽  
Machining Processes ◽  
Coated Tools ◽  
Aisi 1045 Steel ◽  
Aisi 1045 ◽  
1045 Steel ◽  
Rough Turning

Predicting tool-wear (and thereby, tool-life) and selecting proper coated tools along with appropriate tool geometry still remains a major concern for industries trying to achieve increased productivity using automated machining processes. This study is focused upon aggressive high-speed rough turning of AISI 1045 steel. The wear patterns in different coated tools (one mono-layer PVD and two multi-layer CVD coatings) are correlated to changes in nominal tool geometry. This study focuses on the role of tooling geometry (inclination and rake angles) and their importance in dictating the behavior, performance, and wear of coated tools. Using an ‘equivalent toolface’ (ET) model, this study correlates the nominal tool geometry to an equivalent geometry, thereby introducing a new methodology for characterizing the complex effects of multilayer coatings in terms of simple effective tool geometry. The ET approach provides a new angle for understanding the tribological effects of coatings in machining.

scholarly journals Surface Layer States of Worn Uncoated and TiN-Coated WC/Co-Cemented Carbide Cutting Tools after Dry Plain Turning of Carbon Steel

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Johannes Kümmel ◽  
Katja Poser ◽  
Frederik Zanger ◽  
Jürgen Michna ◽  
Volker Schulze
Keyword(s):  
Surface Layer ◽  
Tool Wear ◽  
Tool Life ◽  
Metal Cutting ◽  
Cutting Tools ◽  
Cemented Carbide ◽  
Machining Parameters ◽  
Surface Layers ◽  
Cutting Inserts ◽  
1045 Steel

Analyzing wear mechanisms and developments of surface layers in WC/Co-cemented carbide cutting inserts is of great importance for metal-cutting manufacturing. By knowing relevant processes within the surface layers of cutting tools during machining the choice of machining parameters can be influenced to get less wear and high tool life of the cutting tool. Tool wear obviously influences tool life and surface integrity of the workpiece (residual stresses, surface quality, work hardening, etc.), so the choice of optimised process parameters is of great relevance. Vapour-deposited coatings on WC/Co-cemented carbide cutting inserts are known to improve machining performance and tool life, but the mechanisms behind these improvements are not fully understood. The interaction between commercial TiN-coated and uncoated WC/Co-cemented carbide cutting inserts and a normalised SAE 1045 steel workpiece was investigated during a dry plain turning operation with constant material removal under varied machining parameters. Tool wear was assessed by light-optical microscopy, scanning electron microscopy (SEM), and EDX analysis. The state of surface layer was investigated by metallographic sectioning. Microstructural changes and material transfer due to tribological processes in the cutting zone were examined by SEM and EDX analyses.

scholarly journals Machining of Titanium Metal Matrix Composites: Progress Overview

Materials ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5011
Author(s):  
Cécile Escaich ◽  
Zhongde Shi ◽  
Luc Baron ◽  
Marek Balazinski
Keyword(s):  
Tool Wear ◽  
Tool Life ◽  
Wear Mechanisms ◽  
Metal Matrix ◽  
Dust Emission ◽  
Cutting Speed ◽  
Matrix Composites ◽  
Titanium Metal ◽  
Machining Processes ◽  
Tool Wear Mechanisms

The TiC particles in titanium metal matrix composites (TiMMCs) make them difficult to machine. As a specific MMC, it is legitimate to wonder if the cutting mechanisms of TiMMCs are the same as or similar to those of MMCs. For this purpose, the tool wear mechanisms for turning, milling, and grinding are reviewed in this paper and compared with those for other MMCs. In addition, the chip formation and morphology, the material removal mechanism and surface quality are discussed for the different machining processes and examined thoroughly. Comparisons of the machining mechanisms between the TiMMCs and MMCs indicate that the findings for other MMCs should not be taken for granted for TiMMCs for the machining processes reviewed. The increase in cutting speed leads to a decrease in roughness value during grinding and an increase of the tool life during turning. Unconventional machining such as laser-assisted turning is effective to increase tool life. Under certain conditions, a “wear shield” was observed during the early stages of tool wear during turning, thereby increasing tool life considerably. The studies carried out on milling showed that the cutting parameters affecting surface roughness and tool wear are dependent on the tool material. The high temperatures and high shears that occur during machining lead to microstructural changes in the workpiece during grinding, and in the chips during turning. The adiabatic shear band (ASB) of the chips is the seat of the sub-grains’ formation. Finally, the cutting speed and lubrication influenced dust emission during turning but more studies are needed to validate this finding. For the milling or grinding, there are major areas to be considered for thoroughly understanding the machining behavior of TiMMCs (tool wear mechanisms, chip formation, dust emission, etc.).

Machining

2013 ◽  
pp. 213-270
Keyword(s):  
Electron Beam ◽  
Tool Wear ◽  
Electrical Discharge ◽  
Cutting Fluids ◽  
Machining Parameters ◽  
Machining Processes ◽  
Wire Cutting ◽  
Grinding Operations ◽  
Conventional Machining

Abstract This chapter covers the practical aspects of machining, particularly for turning, milling, drilling, and grinding operations. It begins with a discussion on machinability and its impact on quality and cost. It then describes the dimensional and surface finish tolerances that can be achieved through conventional machining methods, the mechanics of chip formation, the factors that affect tool wear, the selection and use of cutting fluids, and the determination of machining parameters based on force and power requirements. It also includes information on nontraditional machining processes such as electrical discharge, abrasive jet, and hydrodynamic machining, laser and electron beam machining, ultrasonic impact grinding, and electrical discharge wire cutting.

Prediction of Tool Wear Mechanisms in Face Milling AISI 1045 Steel

2011 ◽  
Vol 21 (6) ◽  
pp. 797-808 ◽  
Author(s):  
Patricia Muñoz-Escalona ◽  
Nayarit Díaz ◽  
Zulay Cassier
Keyword(s):  
Tool Wear ◽  
Wear Mechanisms ◽  
Face Milling ◽  
Tool Wear Mechanisms ◽  
Aisi 1045 Steel ◽  
Aisi 1045 ◽  
1045 Steel

Tool Wear Monitoring in Milling Processes Based on Time-Frequency Analysis of Acoustic Emission

2011 ◽  
Vol 141 ◽  
pp. 574-577
Author(s):  
Lu Zhang ◽  
Guo Feng Wang ◽  
Xu Da Qin ◽  
Xiao Liang Feng
Keyword(s):  
Acoustic Emission ◽  
Tool Wear ◽  
Frequency Domain ◽  
Support Vector ◽  
Tool Wear Monitoring ◽  
Machining Processes ◽  
Time Frequency ◽  
Svm Model ◽  
The Status ◽  
Wear Monitoring

Tool wear monitoring plays an important role in the automatic machining processes. Therefore, it is necessary to establish a reliable method to predict tool wear status. In this paper, features of acoustic emission (AE) extracted from time-frequency domain are integrated with force features to indicate the status of tool wear. Meanwhile, a support vector machine (SVM) model is employed to distinguish the tool wear status. The result of the classification of different tool wear status proved that features extracted from time-frequency domain can be the recognize-features of high recognition precision.

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