Evaluation of the Tool Wear the Screw Drill during the Drilling of Stainless Steels DIN 1.4301

2014 ◽  
Vol 692 ◽  
pp. 406-410
Author(s):  
Jozef Jurko ◽  
Anton Panda

This paper presents the conclusions of the cutting tool wear during the drilling of steel DIN 1.4301. Based on the cutting tests, cutting speeds of 40 to 100 m/min, feed rate of 0.05 to 0.5 mm and screw drill carbide monolite. The results of the article are conclusions for working theory and practice for drilling of steel DIN 1.4301.

2013 ◽  
Vol 459 ◽  
pp. 424-427 ◽  
Author(s):  
Jozef Jurko ◽  
Anton Panda

The content of this article also focuses on the analysis of the tool life of screw drills. This paper presents the conclusions of tests on a stainless steel DIN 1.4301.The results of the article are conclusions for working theory and practice for drilling of stainless steels. Based on the cutting tests, cutting speeds of 30 to 60 m/min, feed rate of 0.04to0.1 mm and screw drill carbide monolite.


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.


Materials ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 123 ◽  
Author(s):  
Magdalena Zawada-Michałowska ◽  
Paweł Pieśko ◽  
Jerzy Józwik

The research paper presents the tribological aspects of cutting tool wear during the turning of stainless steels. An experiment was conducted in order to assess the wear of carbide cutting inserts with CVD-applied anti-wear coatings (CNMG 12 04 08 ZSZ and CNMA 12 04 12-KR 3205) and an uncoated ceramic cutting insert (CNGA 12 04 08 T0102 WG 650). The test subject included the following stainless steel grades X20Cr13 (1.4021) and X8CrNiS18-9 (1.4305). The analysis involved the direct wear indicator, VBBmax, and the indirect wear indicator, which was the roughness of machined surfaces and the Ra parameter. Based on the obtained results for both X20Cr13 and X8CrNiS18-9 steels, it was noticed that the best durability was exhibited by the CNMG 12 04 08 ZSZ insert, whereas the worst durability was identified for the CNGA 12 04 08 T0102 WG 650 insert. When analysing the results obtained with the VBBmax direct indicator, it was observed that in the case of each of the insert, most often the course of their wear was of nature similar to linear. Comparing the VBBmax direct indicator with the indirect indicator, namely, the measured Ra parameter, it was concluded that they were convergent. Upon the deterioration of the surface quality, greater values of the selected geometric measure of wear on the flank face were also identified.


2014 ◽  
Vol 599-601 ◽  
pp. 32-35 ◽  
Author(s):  
Jozef Jurko ◽  
Anton Panda ◽  
Iveta Pandová

This paper presents the conclusions the tool wear of screw drill for steel X04Cr16Ni12MnTiN. The results of the article are conclusions for working theory and practice for drilling of steel X04Cr16Ni12MnTiN. Based on the cutting tests, cutting speeds of 50 to 90 m/min, feed rate of 0.02 to 0.8 mm and screw drill carbide monolite. Wear criteria are used in practice. For special cases may also prescribe criteria wear EA (Edge Annihiliation) corresponding to the total destruction of the tip cutting wedge.


2012 ◽  
Vol 224 ◽  
pp. 142-145
Author(s):  
Jozef Jurko ◽  
Anton Panda ◽  
Marcel Behún

This paper presents the conclusions of machinability tests on a XCr18Ni8 stainless steel. The content of this article also focuses on the analysis of selected basic indicators of steel machinability: quality of the processed surface. The results of the article are conclusions for working theory and practice for drillng of austenitic stainless steels. Based on the cutting tests, cutting speeds of 40 to 60 m/min, feed rate of 0.04 to 1.2 mm and screw drill carbide monolite.


2012 ◽  
Vol 500 ◽  
pp. 9-13
Author(s):  
Mário Gajdoš ◽  
Andrej Berdis ◽  
Ján Gecák ◽  
Milan Mičko ◽  
Tadeaš Kurilovský

Precise and reliable information on the machinability of a material before it enters the machining process is a necessity, and hypotheses must be tested through verification of actual methods. This article presents conclusions of machinability tests on a new austenitic stainless steels X2Cr12Ni12MoTiN and describes appropriate parameters for the cutting zone during the process of turning. The content of this article also focuses on the analysis of selected basic indicators of steel machinability: quality of the processed surface. The results of the article are conclusions for working theory and practice for turning of austenitic stainless steels. Based on the cutting tests, cutting speeds of 80 to 200 m/min, feed rate of 0.05 to 0.2 mm and solid carbide insert WNMG 080404-NF.


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.


2014 ◽  
Vol 692 ◽  
pp. 401-405
Author(s):  
Jozef Jurko ◽  
Anton Panda

This paper presents conclusions the machined surface precision of holes for steel DIN 1.4301. Based on the cutting tests, cutting speeds of 40 to 100 m/min, feed rate of 0.05 to 0.5 mm and screw drill carbide monolite. The results of the article are conclusions for working theory and practice for drilling of steel DIN 1.4301.


2014 ◽  
Vol 611-612 ◽  
pp. 452-459 ◽  
Author(s):  
Giovenco Axel ◽  
Frédéric Valiorgue ◽  
Cédric Courbon ◽  
Joël Rech ◽  
Ugo Masciantonio

The present work is motivated by the will to improve Finite Element (FE) Modelling of cutting tool wear. As a first step, the characterisation of wear mechanisms and identification of a wear model appear to be fundamental. The key idea of this work consists in using a dedicated tribometer, able to simulate relevant tribological conditions encountered in cutting (pressure, velocity). The tribometer can be used to estimate the evolution of wear versus time for various tribological conditions (pressure, velocity, temperature). Based on this design of experiments, it becomes possible to identify analytically a wear model. As a preliminary study this paper will be focused on the impact of sliding speed at the contact interface between 304L stainless steel and tungsten carbide (WC) coated with titanium nitride (TiN) pin. This experiment enables to observe a modification of wear phenomena between sliding speeds of 60 m/min and 180 m/min. Finally, the impact on macroscopic parameters has been observed.


1989 ◽  
Vol 111 (3) ◽  
pp. 199-205 ◽  
Author(s):  
S. Y. Liang ◽  
D. A. Dornfeld

This paper discusses the monitoring of cutting tool wear based on time series analysis of acoustic emission signals. In cutting operations, acoustic emission provides useful information concerning the tool wear condition because of the fundamental differences between its source mechanisms in the rubbing friction on the wear land and the dislocation action in the shear zones. In this study, a signal processing scheme is developed which uses an autoregressive time-series to model the acoustic emission generated during cutting. The modeling scheme is implemented with a stochastic gradient algorithm to update the model parameters adoptively and is thus a suitable candidate for in-process sensing applications. This technique encodes the acoustic emission signal features into a time varying model parameter vector. Experiments indicate that the parameter vector ignores the change of cutting parameters, but shows a strong sensitivity to the progress of cutting tool wear. This result suggests that tool wear detection can be achieved by monitoring the evolution of the model parameter vector during machining processes.


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