Experimental Study of Tool Wear Evolution during Turning Operation Based on DWT and RMS

2021 ◽  
Vol 406 ◽  
pp. 392-405
Author(s):  
Hamid Zaida ◽  
Abdelaziz Mahmoud Bouchelaghem ◽  
Seif Eddine Chehaidia
Keyword(s):  
Tool Wear ◽  
Wavelet Transforms ◽  
Cutting Tool ◽  
Flank Wear ◽  
Progressive Failure ◽  
Machining Process ◽  
Discrete Wavelet ◽  
Technical Requirement ◽  
Turning Operation ◽  
Work Material

In cutting process, the wear of the tool remains posed, it describes their progressive failure in regular operation. The tool wear phenomena is mainly caused by abrasion of hard particles, shearing of micro welds between tool and work-material and the exchange of particles between the tool and work material leading to a several forms of tool wear, however, we focused in this study on the frontal wear, also called wear on clearance surface or flank wear. For efficient use of cutting tool according to the technical requirement, the comprehension and the knowledge of the cutting tool wear evolution is necessary. In order to meet this indispensable need, the present paper proposes a two-step tool flank wear monitoring technique based on vibratory signals analysis during the turning operation using a P30 grade metal carbide tool and C45 (XC48) steel. Firstly, discrete wavelet transforms (DWT), has been used to decompose the signal and extract the information, then the scalar indicator Root Mean Square (RMS) value has been used to evaluate the cutting tool stability level. The proposed method offers the possibility to accurately predict break-in tool wear phase, accelerated tool wear phase and the stability period, in which a high quality machining process is guaranteed.

scholarly journals Vibration–Based online Tool Wear Monitoring Using Piezo Film Sensor Analyzed by I-kaz Multilevel Signal Feature

2019 ◽  
Vol 8 (6) ◽  
pp. 3397-3403
Keyword(s):  
Tool Wear ◽  
Monitoring System ◽  
Cutting Tool ◽  
Flank Wear ◽  
Vibration Signal ◽  
Machining Process ◽  
Digital Data ◽  
Current Status ◽  
Tool Holder ◽  
Multilevel Signal

Wear in cutting tool is a normal phenomenon in machining process. Problems such as dimensional precision, surface finish quality and defect cost is due to the wear. The wear also can cause unexpected stop time and lower down the manufacturing productivity. Therefore, a system to monitor the progression of the tool wear is needed to predict the wear status and stop machining operation once the wear reach the allowed limit. In this study, the monitoring system was designed by utilizing 2 units of piezoelectric film sensors which are capable of detecting and analyzing signals related to tool holder vibration during the machining process in both feed and tangential axes. The sensors were stacked on x axis and z axis surfaces of the tool holder and signals were channeled to a charge amplifier and then to the digital data acquisition equipment which then display the vibration signal in time domain on the computer screen. A total of 8 experiments were carried out using CNC turning machine. Vibration signal and wear measurement were recorded for each run in the experiment. The experiment were stopped once the wear reach approximately 0.3mm. I-kaz multilevel signal features were extracted from the vibration signal recorded and then correlated with the flank wear status. There is a solid or substantial correlation between the cutting tool wear condition and I-kaz multilevel coefficient value, with average of 0.87 for I-kaz x coefficient (tangential direction) and 0.910 for I-kaz z coefficient (feed direction). This affirm that I-kaz multilevel signal feature can be assigned as the input criterion for the tool condition monitoring system that can estimate the current status of the flank wear on the cutting tools which can prevent defect in the machining process

scholarly journals A Novel Computer Vision Based Machine Learning Approach For Online Tool Wear Monitoring In Machining

2021 ◽  
Author(s):  
Prashant J Bagga ◽  
Mayur A. Makhesana ◽  
Adarsh D. Pala ◽  
Kavan C. Chauhan ◽  
Kaushik M Patel
Keyword(s):  
Machine Learning ◽  
Computer Vision ◽  
Tool Wear ◽  
Cutting Tool ◽  
Flank Wear ◽  
Cnc Machining ◽  
Machining Process ◽  
Support Vector ◽  
Tool Insert ◽  
Wear Measurement

Abstract With the increased scope of automated machining processes, one of the essential requirements is the reliable predictions of the tool life. It is crucial to monitor the condition of the cutting tool during the machining process to achieve high-quality machining and cost-effective production. This paper presents a computer vision technique for flank wear measurement and prediction using machine learning, specifically support vector machine (SVM) and boosted decision trees has been used. The proposed methodology for tool wear measurement is illustrated for the CNC machining experimentally. The direct method of tool wear measurement and prediction have been proposed. Flank wear measurement is carried out on PVD coated tool insert, and experiments are performed on an alloy steel workpiece under dry machining. For capturing images, a CMOS camera with a lens mounted on the machine is used. To avoid environmental effects on the images LED ring light is used. Captured tool insert images are provided to the image processing algorithm built-in MATLAB software. The measurement of flank wear is also carried out using a microscope. The prediction accuracy of SVM and optimized boosted tree models is 97% and 96%, respectively, proving prediction algorithms' effectiveness. The findings showcased that the proposed methodology can measure and predict the tool wear with higher accuracy. It has demonstrated the ability to increase cutting tool utilization with the improved surface finish of the machined component.

scholarly journals A Novel Finite Element Method Approach in the Modelling of Edge Trimming of CFRP Laminates

2021 ◽  
Vol 11 (11) ◽  
pp. 4743
Author(s):  
Fernando Cepero-Mejias ◽  
Nicolas Duboust ◽  
Vaibhav A. Phadnis ◽  
Kevin Kerrigan ◽  
Jose L. Curiel-Sosa
Keyword(s):  
Finite Element ◽  
Tool Wear ◽  
Cutting Tool ◽  
Machining Process ◽  
Machining Forces ◽  
General Terms ◽  
Numerical Predictions ◽  
Composite Damage ◽  
Edge Trimming ◽  
Optimal Cutting Parameters

Nowadays, the development of robust finite element models is vital to research cost-effectively the optimal cutting parameters of a composite machining process. However, various factors, such as the high computational cost or the complicated nature of the interaction between the workpiece and the cutting tool significantly hinder the modelling of these types of processes. For these reasons, the numerical study of common machining operations, especially in composite machining, is still minimal. This paper presents a novel approach comprising a mixed multidirectional composite damage mode with composite edge trimming operation. An ingenious finite element framework which infer the cutting edge tool wear assessing the incremental change of the machining forces is developed. This information is essential to replace tool inserts before the tool wear could cause severe damage in the machined parts. Two unidirectional carbon fibre specimens with fibre orientations of 45∘ and 90∘ manufactured by pre-preg layup and cured in an autoclave were tested. Excellent machining force predictions were obtained with errors below 10% from the experimental trials. A consistent 2D FE composite damage model previously performed in composite machining was implemented to mimic the material failure during the machining process. The simulation of the spring back effect was shown to notably increase the accuracy of the numerical predictions in comparison to similar investigations. Global cutting forces simulated were analysed together with the cutting tool tooth forces to extract interesting conclusions regarding the forces received by the spindle axis and the cutting tool tooth, respectively. In general terms, vertical and normal forces steadily increase with tool wear, while tangential to the cutting tool, tooth and horizontal machining forces do not undergo a notable variation.

Cutting Tool Wear and Mechanisms of Chip Formation During High-Speed Machining of Compacted Graphite Iron

2007 ◽  
Author(s):  
Niniza S. P. Dlamini ◽  
Iakovos Sigalas ◽  
Andreas Koursaris
Keyword(s):  
Tool Wear ◽  
Surface Finish ◽  
Failure Criterion ◽  
Cutting Tool ◽  
Flank Wear ◽  
Cutting Tools ◽  
Compacted Graphite Iron ◽  
Crater Wear ◽  
Compacted Graphite ◽  
Cutting Speeds

Cutting tool wear of polycrystalline cubic boron nitride (PcBN) tools was investigated in oblique turning experiments when machining compacted graphite iron at high cutting speeds, with the intention of elucidating the failure mechanisms of the cutting tools and presenting an analysis of the chip formation process. Dry finish turning experiments were conducted in a CNC lathe at cutting speeds in the range of 500–800m/min, at a feed rate of 0.05mm/rev and depth of cut of 0.2mm. Two different tool end-of-life criteria were used: a maximum flank wear scar size of 0.3mm (flank wear failure criterion) or loss of cutting edge due to rapid crater wear to a point where the cutting tool cannot machine with an acceptable surface finish (surface finish criterion). At high cutting speeds, the cutting tools failed prior to reaching the flank wear failure criterion due to rapid crater wear on the rake face of the cutting tools. Chip analysis, using SEM, revealed shear localized chips, with adiabatic shear bands produced in the primary and secondary shear zones.

scholarly journals Comparison contact and thermal imaging methods measure the temperatures of the turning blades during cutting

Mechanik ◽  
2017 ◽  
Vol 90 (3) ◽  
pp. 214-216
Author(s):  
Karol Grochalski ◽  
Piotr Jabłoński
Keyword(s):  
Tool Wear ◽  
Thermal Imaging ◽  
Cutting Tool ◽  
Processing Parameters ◽  
Machining Process ◽  
Influence Of Temperature ◽  
Imaging Methods ◽  
Advantages And Disadvantages ◽  
Influence Of Temperature On ◽  
Materials Used

The paper presents a method of measuring the temperature during cutting and its impact on the machining process. The influence of temperature on the intensity of the cutting tool wear cutting and durability. Shows the measuring position, the materials used and the cutting tool. We present the results of the processing parameters, during which the measurements are made. This paper presents methods for measuring the temperature of the blade using a thermocouple and methods of radiation. It lists the advantages and disadvantages of each method.

Tool Wear Analysis of MTConnect Production Data

2021 ◽  
Author(s):  
David Stock ◽  
Aditi Mukhopadhyay ◽  
Rob Potter ◽  
Andy Henderson
Keyword(s):  
Tool Wear ◽  
Cutting Tool ◽  
Numerical Control ◽  
Machining Process ◽  
Total Load ◽  
Wear Rates ◽  
Wear Analysis ◽  
Nc Program ◽  
Small Set ◽  
Key Steps

Abstract This paper presents the analysis of data collected using the MTConnect protocol from a lathe with a Computer Numerical Control (CNC). The purpose of the analysis is to determine an estimated cutting tool life and generate a model for calculating a real-time proxy of cutting tool wear. Various streams were used like spindle load, NC program blocks, the mode, execution etc. The novelty of this approach is that no information about the machining process, beyond the data provided by the machine, was necessary to determine the tool’s expected life. This method relies on the facts that a) it is generally accepted cutting loads increase with tool wear and b) that many CNC machines rely on a small set of regularly run CNC programs. These facts are leveraged to extract the total load for each run of each program on the machine, creating a dataset which is a good indicator of tool wear and replacement. The presented methodology has four key steps: extracting cycle metadata from the machine execution data; computing the integrated spindle loads for every cycle; normalizing the integrated spindle loads between different programs; extracting tool wear rates and changes from the resulting dataset. It is shown that the method can successfully extract the signature of tool wear under a common set of circumstances which are discussed in detail.

Performance of Low Cost 3D Printed Minimum Quantity Lubrication Applicator Using Palm Oil in Milling Steel

2020 ◽  
Vol 997 ◽  
pp. 85-92
Author(s):  
Abang Mohammad Nizam Abang Kamaruddin ◽  
Abdullah Yassin ◽  
Shahrol Mohamaddan ◽  
Syaiful Anwar Rajaie ◽  
Muhammad Isyraf Mazlan ◽  
...  
Keyword(s):  
Tool Wear ◽  
Cutting Forces ◽  
Cutting Tool ◽  
Low Cost ◽  
Minimum Quantity Lubrication ◽  
Machining Process ◽  
Cutting Condition ◽  
Dry Cutting ◽  
Minimum Quantity ◽  
Tool Performance

One of the most significant factors in machining process or metal cutting is the cutting tool performance. The rapid wear rate of cutting tools and cutting forces expend due to high cutting temperature is a critical problem to be solved in high-speed machining process, milling. Near-dry machining such as minimum quantity lubrication (MQL) is regarded as one of the solutions to solve this problem. However, the function of MQL in milling process is still uncertain so far which prevents MQL from widely being utilized in this specific machining process. In this paper, the mechanism of cutting tool performance such as tool wear and cutting forces in MQL assisted milling is investigated more comprehensively and the results are compared in three different cutting conditions which is dry cutting, wet cutting (flooding) and MQL. The MQL applicator is constructed from a household grade low-cost 3D printing technique. The chips surface of chips formation in each cutting condition is also observed using Scanning Electron Microscopy (SEM) machine. It is found out that wet cutting (flooding) is the best cutting performance compare to MQL and dry cutting. However, it can also be said that wet cutting and MQL produced almost the same value of tool wear and cutting forces as there is negligible differences in average tool wear and cutting forces between them based on the experiment conducted.

scholarly journals Experimental Study on Tool Wear and Delamination in Milling CFRPs with TiAlN- and TiN-Coated Tools

Coatings ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 623 ◽  
Author(s):  
Dervis Ozkan ◽  
Peter Panjan ◽  
Mustafa Sabri Gok ◽  
Abdullah Cahit Karaoglanli
Keyword(s):  
Tool Wear ◽  
Cutting Tool ◽  
Failure Mechanisms ◽  
Cutting Tools ◽  
Machining Process ◽  
Dynamic Loads ◽  
Fiber Reinforced Polymers ◽  
Machining Parameters ◽  
Coated Tool ◽  
Cfrp Composite

Carbon fiber-reinforced polymers (CFRPs) have very good mechanical properties, such as extremely high tensile strength/weight ratios, tensile modulus/weight ratios, and high strengths. CFRP composites need to be machined with a suitable cutting tool; otherwise, the machining quality may be reduced, and failures often occur. However, as a result of the high hardness and low thermal conductivity of CFRPs, the cutting tools used in the milling process of these materials complete their lifetime in a short cycle, due to especially abrasive wear and related failure mechanisms. As a result of tool wear, some problems, such as delamination, fiber breakage, uncut fiber and thermal damage, emerge in CFRP composite under working conditions. As one of the main failure mechanisms emerging in the milling of CFRPs, delamination is primarily affected by the cutting tool material and geometry, machining parameters, and the dynamic loads arising during the machining process. Dynamic loads can lead to the breakage and/or wear of cutting tools in the milling of difficult-to-machine CFRPs. The present research was carried out to understand the influence of different machining parameters on tool abrasion, and the work piece damage mechanisms during CFRP milling are experimentally investigated. For this purpose, cutting tests were carried out using a (Physical Vapor Deposition) PVD-coated single layer TiAlN and TiN carbide tool, and the abrasion behavior of the coated tool was investigated under dry machining. To understand the wear process, scanning electron microscopy (SEM) equipped with energy-dispersive X-ray spectroscopy (EDS) was used. As a result of the experiments, it was determined that the hard and abrasive structure of the carbon fibers caused flank wear on TiAlN- and TiN-coated cutting tools. The best machining parameters in terms of the delamination damage of the CFRP composite were obtained at high cutting speeds and low feed rates. It was found that the higher wear values were observed at the TiAlN-coated tool, at the feed rate of 0.05 mm/tooth.

Designing and implementation of a novel online adaptive control with optimization technique in hard turning

2020 ◽  
pp. 095965182095219
Author(s):  
Vahid Pourmostaghimi ◽  
Mohammad Zadshakoyan
Keyword(s):  
Adaptive Control ◽  
Tool Wear ◽  
Hard Turning ◽  
Cutting Tool ◽  
Optimization Technique ◽  
Cutting Parameters ◽  
Numerical Control ◽  
Machining Process ◽  
Machining Parameters ◽  
Optimization Methodology

Determination of optimum cutting parameters is one of the most essential tasks in process planning of metal parts. However, to achieve the optimal machining performance, the cutting parameters have to be regulated in real time. Therefore, utilizing an intelligent-based control system, which can adjust the machining parameters in accordance with optimal criteria, is inevitable. This article presents an intelligent adaptive control with optimization methodology to optimize material removal rate and machining cost subjected to surface quality constraint in finish turning of hardened AISI D2 considering the real condition of the cutting tool. Wavelet packet transform of cutting tool vibration signals is applied to estimate tool wear. Artificial intelligence techniques (artificial neural networks, genetic programming and particle swarm optimization) are used for modeling of surface roughness and tool wear and optimization of machining process during hard turning. Confirmatory experiments indicated that the efficiency of the proposed adaptive control with optimization methodology is 25.6% higher compared to the traditional computer numerical control turning systems.

Investigation on Chip Formation during Machining Using Finite Element Modeling

2012 ◽  
Vol 505 ◽  
pp. 31-36 ◽  
Author(s):  
Moaz H. Ali ◽  
Basim A. Khidhir ◽  
Bashir Mohamed ◽  
A.A. Oshkour
Keyword(s):  
Finite Element ◽  
Tool Wear ◽  
Finite Element Modeling ◽  
Chip Formation ◽  
Cutting Tool ◽  
Chip Morphology ◽  
Machining Process ◽  
Element Modeling ◽  
Segmented Chip ◽  
Cutting Speeds

Titanium alloys are desirable materials for aerospace industry because of their excellent combination of high specific strength, lightweight, fracture resistant characteristics, and general corrosion resistance. Therefore, the chip morphology is very important in the study of machinability of metals as well as the study of cutting tool wear. The chips are generally classified into four groups: continuous chips, chips with built-up-edges (BUE), discontinuous chips and serrated chips. . The chip morphology and segmentation play a predominant role in determining machinability and tool wear during the machining process. The mechanics of segmented chip formation during orthogonal cutting of titanium alloy Ti–6Al–4V are studied in detail with the aid of high-speed imaging of the chip formation zone. The finite element model of chip formation of Ti–6Al–4V is suggested as a discontinuous type chip at lower cutting speeds developing into a continuous, but segmented, chip at higher cutting speeds. The prediction by using finite-element modeling method and simulation process in machining while create chips formation can contribute in reducing the cost of manufacturing in terms of prolongs the cutting tool life and machining time saving.

Sign in / Sign up

Export Citation Format

Share Document