scholarly journals System for Tool-Wear Condition Monitoring in CNC Machines under Variations of Cutting Parameter Based on Fusion Stray Flux-Current Processing

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8431
Author(s):  
Arturo Yosimar Jaen-Cuellar ◽  
Roque Alfredo Osornio-Ríos ◽  
Miguel Trejo-Hernández ◽  
Israel Zamudio-Ramírez ◽  
Geovanni Díaz-Saldaña ◽  
...  

The computer numerical control (CNC) machine has recently taken a fundamental role in the manufacturing industry, which is essential for the economic development of many countries. Current high quality production standards, along with the requirement for maximum economic benefits, demand the use of tool condition monitoring (TCM) systems able to monitor and diagnose cutting tool wear. Current TCM methodologies mainly rely on vibration signals, cutting force signals, and acoustic emission (AE) signals, which have the common drawback of requiring the installation of sensors near the working area, a factor that limits their application in practical terms. Moreover, as machining processes require the optimal tuning of cutting parameters, novel methodologies must be able to perform the diagnosis under a variety of cutting parameters. This paper proposes a novel non-invasive method capable of automatically diagnosing cutting tool wear in CNC machines under the variation of cutting speed and feed rate cutting parameters. The proposal relies on the sensor information fusion of spindle-motor stray flux and current signals by means of statistical and non-statistical time-domain parameters, which are then reduced by means of a linear discriminant analysis (LDA); a feed-forward neural network is then used to automatically classify the level of wear on the cutting tool. The proposal is validated with a Fanuc Oi mate Computer Numeric Control (CNC) turning machine for three different cutting tool wear levels and different cutting speed and feed rate values.

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Harun Gokce

Stainless steels with unique corrosion resistance are used in applications with a wide range of fields, especially in the medical, food, and chemical sectors, to maritime and nuclear power plants. The low heat conduction coefficient and the high mechanical properties make the workability of stainless steel materials difficult and cause these materials to be in the class of hard-to-process materials. In this study, suitable cutting tools and cutting parameters were determined by the Taguchi method taking surface roughness and cutting tool wear into milling of Custom 450 martensitic stainless steel. Four different carbide cutting tools, with 40, 80, 120, and 160 m/min cutting speeds and 0.05, 0.1, 0.15, and 0.2 mm/rev feed rates, were selected as cutting parameters for the experiments. Surface roughness values and cutting tool wear amount were determined as a result of the empirical studies. ANOVA was performed to determine the significance levels of the cutting parameters on the measured values. According to ANOVA, while the most effective cutting parameter on surface roughness was the feed rate (% 50.38), the cutting speed (% 81.15) for tool wear was calculated.


2011 ◽  
Vol 188 ◽  
pp. 319-324
Author(s):  
Hao Yang ◽  
Xi Bin Wang ◽  
Li Jing Xie ◽  
J.J. Pei ◽  
T. Wang

By dry cutting 34CrNiMo6, hard-machined material, with carbide cutting tool and ceramic cutting tool, experimental analysis was carried out in tool wear and cutting force. Cutting tool wear in the process is researched in order to obtain the cutting tool wear patterns and analyze the influencing factors. Meanwhile, it is found that the cutting force with the cutting parameters (cutting speed, cutting depth, feed) changes regularly, and then the experience formula of cutting force can be established.


2020 ◽  
Author(s):  
Ömer ŞAHİN ◽  
Erdinç KALUÇ

Abstract In this study, effects of feed rate and cutting speed on surface roughness and cutting tool wear were investigated in drilling of AISI 4140 tempered steel workpieces with internally cooled, Ø14 mm diameter solid carbide drills on a CNC lathe. Although there are various literature on this subject, since there is no information on the experimental parameters that the study has been done, the contribution and originality of the study to the literature is to be qualitative.The experimental study was conducted using cooling water and with cutting speeds of 50, 60, 70, and 80 m/min and feed rate parameters of 0.10, 0.15, 0.20, and 0.25 mm/rev. At the end of the experiment, wear of the used drills was monitored with a material microscope and wear values were determined. Surface roughness of the holes was measured with Mitutoyo branded surface roughness measurement instrument. The longest drill life was obtained at 50 m/min cutting speed and 0.10 mm/rev feed rate. Surface roughness of the samples with drilled holes was measured, and these values were found to vary in the range of 0.270–2.480 µm. At 0.10 mm/rev feed rate and 50 m/min cutting speed, the lowest cutting tool wear was measured as 1222393.74 µm2, while the highest wear was measured as 4532811.14 µm2. For the best surface quality and lowest cutting tool wear, 50 m/min cutting speed and 0.10 mm/rev feed rate were determined to be the optimum parameters.


2021 ◽  
Author(s):  
Hüseyin Gürbüz ◽  
Şehmus Baday

Abstract Although Inconel 718 is an important material for modern aircraft and aerospace, it is a kind material, which is known to have low machinability. Especially, while these types of materials are machined, high cutting temperatures, BUE on cutting tool, high cutting forces and work hardening occur. Therefore, in recent years, instead of producing new cutting tools that can withstand these difficult conditions, cryogenic process, which is a heat treatment method to increase the wear resistance and hardness of the cutting tool, has been applied. In this experimental study, feed force, surface roughness, vibration, cutting tool wear, hardness and abrasive wear values that occurred as a result of milling of Inconel 718 material by means of cryogenically treated and untreated cutting tools were investigated. Three different cutting speeds (35-45-55 m/min) and three different feed rates (0.02-0.03-0.04 mm/tooth) at constant depth of cut (0.2 mm) were used as cutting parameters in the experiments. As a result of the experiments, lower feed forces, surface roughness, vibration and cutting tool wear were obtained with cryogenically treated cutting tools. As the feed rate and cutting speed were increased, it was seen that surface roughness, vibration and feed force values increased. At the end of the experiments, it was established that there was a significant relation between vibration and surface roughness. However, there appeared an inverse proportion between abrasive wear and hardness values. While BUE did not occur during cryogenically treated cutting tools, it was observed that BUE occurred in cutting tools which were not cryogenically treated.


Author(s):  
Vahid Pourmostaghimi ◽  
Mohammad Zadshakoyan

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.


Metals ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 1014 ◽  
Author(s):  
Sánchez Hernández ◽  
Trujillo Vilches ◽  
Bermudo Gamboa ◽  
Sevilla Hurtado

In this work, the analysis of the cutting speed and feed rate influence on tool wear and cutting forces in Ti6Al4V alloy dry machining is presented. The study has been focused on the machining in a transient state. The tool wear mechanisms, tool wear intensity and cutting forces evolution have been analyzed as a function of the cutting parameters. Experimental results show that the main cutting force amplitude exhibits a general trend to increase with both cutting parameters. Crater wear was more evident at high cutting speeds, whereas flank wear was present on the whole interval of the cutting parameters analyzed. Furthermore, the cutting speed shows a slightly higher influence on crater wear and the feed rate shows a higher influence on flank wear. Finally, several experimental parametric models have been obtained. These models allow predicting the evolution of crater and flank tool wear, as well as the cutting forces, as a function of the cutting parameters. Additionally, a model that allows monitoring the tool wear on the machining transient state as a function of the main cutting force amplitude has been developed.


2010 ◽  
Vol 26-28 ◽  
pp. 1052-1055
Author(s):  
Li Fa Han ◽  
Sheng Guan Qu

The wear characteristics and life of Al2O3/(W,Ti)C ceramic tool in turning NbCp-reinforced iron-based P/M composites was investigated. Experimental results indicate that cutting parameters have an influence on tool wear, among which cutting speed and depth of cut seem to be more prominent. The maximum flank wear rapidly increases as the increase in cutting speed and depth of cut. While, it increases gradually as the decrease in feed rate. Meanwhile, an empirical model of tool life is established, from which the influence of cutting speed and depth of cut on tool life is far greater than that of feed rate. Also from the empirical model, the preferable range of cutting parameters was obtained.


2020 ◽  
Vol 17 (2) ◽  
pp. 961-966
Author(s):  
Allina Abdullah ◽  
Afiqah Azman ◽  
B. M. Khirulrizwan

This research outlines an experimental study to determine the optimum parameter of cutting tool for the best surface roughness (Ra) of Aluminum Alloy (AA) 6063. For the experiment in this research, cutting parameters such as cutting speed, depth of cut and feed rate are used to identify the effect of both cutting tools which are tungsten carbide and cermet towards the surface roughness (Ra) of material AA6063. The machining operation involved to cut the material is turning process by using Computer Numerical Control (CNC) Lathe machine. The experimental design was designed by Full Factorial. The experiment that had been conducted by the researcher is 33 with 2 replications. The total number of the experiments that had been run is 54 runs for each cutting tool. Thus, the total number of experiments for both cutting tools is 108 runs. ANOVA analysis had been analyzed to identify the significant factor that affect the Ra result. The significant factors that affect the Ra result of AA6063 are feed rate and cutting speed. The researcher used main effect plot to determine the factor that most influenced the surface roughness of AA6063, the optimum condition of surface roughness and the optimum parameter of cutting tool. The factor that most influenced the surface roughness of AA6063 is feed rate. The optimum condition of surface roughness is at the feed rate of 0.05 mm/rev, cutting speed of 600 rpm and depth of cut of 0.10 mm. While the optimum parameter of cutting tool is cermet insert with the lowest value of surface roughness (Ra) result which is 0.650 μm.


2013 ◽  
Vol 773-774 ◽  
pp. 339-347 ◽  
Author(s):  
Muhammad Yusuf ◽  
M.K.A. Ariffin ◽  
N. Ismail ◽  
S. Sulaiman

With increasing quantities of applications of Metal Matrix Composites (MMCs), the machinablity of these materials has become important for investigation. This paper presents an investigation of surface roughness and tool wear in dry machining of aluminium LM6-TiC composite using uncoated carbide tool. The experiments carried out consisted of different cutting models based on combination of cutting speed, feed rate and depth of cut as the parameters of cutting process. The cutting models designed based on the Design of Experiment Response Surface Methodology. The objective of this research is finding the optimum cutting parameters based on workpiece surface roughness and cutting tool wear. The results indicated that the optimum workpiece surface roughness was found at high cutting speed of 250 m min-1 with various feed rate within range of 0.05 to 0.2 mm rev-1, and depth of cut within range of 0.5 to 1.5 mm. Turning operation at high cutting speed of 250 m min-1 produced faster tool wear as compared to low cutting speed of 175 m min-1 and 100 m min-1. The wear minimum (VB = 42 μm ) was found at cutting speed of 100 m min-1, feet rate of 0.2 mm rev-1, and depth of cut of 1.0 mm until the length of cut reached 4050 mm. Based on the results of the workpiece surface roughness and the tool flank wear, recommended that turning of LM6 aluminium with 2 wt % TiC composite using uncoated carbide tool should be carried out at cutting speed higher than 175 m min-1 but at feed rate of less than 0.05 mm rev-1 and depth of cut less than 1.0 mm.


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