A Comparative Thermal Analysis of Two Workpiece Materials of Different Machinability When Turning Based on Ir Thermography
1
Department of Machine Design and Maintenance, AGH University of Krakow, Poland
2
Department of Transport Equipment and Technologies , S. Seifullin Kazakh Agro Technical Research University, Kazakhstan
3
Department of Organization of Transport, Traffic and Transport Operations, L.N. Gumilyov Eurasian National University, Kazakhstan
4
Department of Technological Machines and Equipment, S.Seifullin Kazakh Agro Technical Research University, Kazakhstan
5
Department of Manufacturing Systems, AGH University of Krakow, Poland
Submission date: 2024-01-12
Final revision date: 2024-02-15
Acceptance date: 2024-02-25
Online publication date: 2024-03-08
Publication date: 2024-04-02
Corresponding author
Michał Bembenek
Department of Manufacturing Systems, AGH University of Krakow, Al. Mickiewicza 30, 30-059, Kraków, Poland
Department of Manufacturing Systems, AGH University of Krakow, Al. Mickiewicza 30, 30-059, Kraków, Poland
Journal of Machine Engineering 2024;24(1):50-59
KEYWORDS
TOPICS
ABSTRACT
The comparative thermography analysis of temperature during machining by turning was presented. For the tests cast iron EN-GJL 250 and stainless steel 1.4301 were used. The machining by turning was performed with the TNMG 220408HS PC9030 and TNMA 220208 NC6210 cutting inserts design for machining that kind of materials. The temperature was measured on the machined material and on the surface of the cutting insert. The temperature distribution was performed during 3 subsequent turning passes; therefore, the coolant was not used during machining. The emissivity of TNMG 220408HS PC9030 and TNMA 220208 NC6210 cutting inserts was performed. In the case of EN-GJL-250 cast iron, the tests have shown that due to safety reasons (the lack of the safety cover in the working area of the lathe) it was impossible to perform the measurements at the highest assumed machining speed of 339.1 m/min. The higher average temperatures in the cmaterial were recorded for 1.4301 steel, even though the machining process was performed at a much lower machining speed than in the case of EN-GJL-250 cast iron. The average cutting insert temperature when turning EN-GJL-250 cast iron was approximately 100°C higher than for 1.4301 steel.
REFERENCES (44)
1.
MINKINA W., 2021, How Infrared Radiation Was Discovered—Range of This Discovery and Detailed, Appl. Sci., 11, 9824, https://doi.org/10.3390/app112....
2.
SZAJEWSKA A., 2017, Development of the Thermal Imaging Camera (TIC) Technology, Procedia Engineering, 172, 2017, 1067–1072, https://doi.org/10.1016/j.proe....
3.
KIM H., LAMICHHANE N., KIM C, SHRESTHA R., 2023, Innovations in Building Diagnostics and Condition Monitoring: A Comprehensive Review of Infrared Thermography Applications, Buildings, 13, 2829, https://doi.org/10.3390/buildi....
4.
TOMITA K., CHEW M.Y.L., 2022, A Review of Infrared Thermography for Delamination Detection on Infrastructures and Buildings, Sensors, 22, 423, https://doi.org/10.3390/s22020....
5.
BORAWSKI A., 2019, Common Methods in Analysing the Tribological Properties of Brake Pads and Discs – a Review, Acta Mechanica et Automatica, 13/3, 189–199.
6.
YOUSUF A., KHAWAJA H., VIRK M.S., 2024, A Review of Infrared Thermography Applications for ice detection and mitigation, Cold Regions Science and Technology, 218, 10458.
7.
KAMPCZYK A., GAMON W., GAWLAK K., 2022, Implementation of Non-Contact Temperature Distribution Monitoring Solutions for Railway Vehicles in a Sustainability Development System Transport, Sensors, 22. 9624, https://doi.org/10.3390/s22249....
8.
BUCHCZIK D., BUDZAN S., KRAUZE O., WYZGOLIK R., 2023, Moisture Determination for Fine-Sized Copper Ore by Computer Vision and Thermovision Methods, Sensors, 23, 1220, https://doi.org/10.3390/s23031....
9.
OWENS A., KANDLIKAR S.G., PHATAK P., 2021, Potential of Infrared Imaging for Breast Cancer Detection: A Critical Evaluation, ASME J. of Medical Diagnostics, 4/4, 041005.
10.
KAPJOR A., SMATANOVA H., HUZVAR J., GRESSAK T., JANDACKA J., 2013, Optimization of Heat Transfer Oriented Surfaces by Thermovision and Using CFD Method, Structure and Environment, 5/4, 41–44.
11.
KALACZYNSKI T., LUKASIEWICZ M., MUSIAL J., LISS M., KASPROWICZ T.B., 2020, Analysis of the Diagnostic Potential Thermovision Research in the Technical Condition Assessment of Spark Ignition Engines Injectors, Engineering Mechanics, 26, 262–265.
12.
PIECUCH G., MADERA M, ZABINSKI T., 2019, Diagnostics of Welding Process Based on Thermovision Images Using Convolutional Neural Network, IOP Conference Series: Materials Science and Engineering, 710/1.
13.
WANG R., ZHAN X., BAI H., DONG E., CHENG Z., JIA X., 2022, A Review of Fault Diagnosis Methods for Rotating Machinery Using Infrared Thermography, Micromachines, 13, 1644.
14.
MEZYK J., 2015, Monitoring Material Joining Processes with use of Advanced Vision Methods, Maintenance Problems, 1/96, 37–46.
15.
SWIC A., WOLOS D., ZUBRZYCKI J., OPIELAK M., GOLA A., TARANENKO V., 2014, Accuracy Control in the Machining of Low Rigidity Shafts, Applied Mechanics and Materials, 613, 357–367.
16.
BYRNE G., DORNFELD D., DENKENA B., 2003, Advancing Cutting Technology, CIRP Annals, 52/2, 483–507.
17.
SENTHILKUMAR N., GANAPATHY T., TAMIZHARASAN T., 2014, Optimisation of Machining and Geometrical Parameters in Turning Process Using Taguchi Method. Australian Journal of Mechanical Engineering, 12/2, 233–246.
18.
BEMBENEK M., KUDELSKI R., PAWLIK J., KOWALSKI Ł., 2021, The Influence of CNC Turning with VBMT, RCMX, 3ER, and MGMN Type Indexable Inserts on West African Ebony/Diospyros Crassiflora, San Domingo Boxwood/Phyllostylon Brasiliense, Rio Rosewood/Dalbergia Nigra, Beechwood/Fagus Sylvatica, Oakwood/Quercus Robur, and Pinewood/Pinus Silvestris Surface Roughness. Materials, 14, 5625.
19.
PANWAR V., SHARMA D.K., PRADEEP K.V., JAIN A., THAKAR Ch., 2021, Experimental Investigations and Optimization of surface roughness in turning of en 36 alloy steel using response surface methodology and genetic algorithm, Materials today: proceedings, 46, 6474–6481.
20.
DOAN T.K., NGUYEN T.T., VAN. A.L, 2023, Multi-Objective Optimization of the Rotary Turning of Hardened Mold Steel for Energy Saving and Surface Roughness Improvements, Journal of Machine Engineering. 23/4, 101–121, https://doi.org/10.36897/jme/1....
21.
QEHAJA N., JAKUPI K., BUNJAKU A., BRUÇI M., OSMANI H., 2015, Effect of Machining Parameters and Machining Time on Surface Roughness in Dry Turning Process. Procedia Engineering, 100, 135–140.
22.
ZHAO G.Y., LIU Z.Y., HE Y., CAO H. J., GUO Y.B., 2017, Energy Consumption in Machining: Classification, Prediction, and Reduction Strategy, Energy, 133, 142–157.
23.
SHROUF F., ORDIERES-MERE J., GARCIA-SANCHEZ A., ORTEGA-MIER M., 2014, Optimizing the production scheduling of a single machine to minimize total energy consumption costs, Journal of Cleaner Production, 67, 197-207.
24.
GRZESIK W., 2020, Modelling of Heat Generation and Transfer in Metal Cutting: a Short Review, Journal of Machine Engineering. 20/1, 24–33, https://doi.org/10.36897/jme/1....
25.
NIESŁONY P., GRZESIK W., LASKOWSKI P., ZAK K., 2015, Numerical 3D Simulation and Experimental Analysis of Tribological Aspects in Turning Inconel 718 alloy, Journal of Machine Engineering, 15/1, 47–57.
26.
SHEROV K., MUSSAYEV M., USSERBAYEV M., MAGAVIN S., ABISHEVA N., KARSAKOVA N., MYRZAKHMET B., 2022, Investigation of the Method of Thermal Friction Turn-Milling of High Strength Materials, Journal of Applied Engineering Science, 20/1, 13–18.
27.
TATSIY R.M., PAZEN O.Y., VOVK S.Y. ROPYAK L.Y., PRYHOROVSKA T.O., 2019, Numerical Study on Heat Transfer in Multilayered Structures of Main Geometric Forms Made of Different Materials, Journal of the Serbian Society for Computational Mechanics, 13/2, 36–55.
28.
GRZESIK W., RECH J., ZAK K., CLAUDIN C., Machining Performance of Pearlitic–Ferritic Nodular Cast Iron with Coated Carbide and Silicon Nitride Ceramic Tools, International Journal of Machine Tools and Manufacture, 49/2, 125–133.
29.
JAFARIAN F., CIARAN M.I., UMBRELLO D., ARRAZOLA P.J., FILICE L., AMIRABADI H., 2014, Finite element simulation of machining Inconel 718 Alloy Including Microstructure Changes, International Journal of Mechanical Sciences, 88, 110–121.
30.
WANG F., ZHAO J., LI A., ZHANG H., 2014, Effects of Cutting Conditions on Microhardness and Microstructure in High-Speed Milling of H13 Tool Steel, The International Journal of Advanced Manufacturing Technology, 73, 137–146.
31.
BEMBENEK M., KOPEI V., ROPYAK L., LEVCHUK K., 2023, Stressed State of Chrome Parts During Diamond Burnishing, Metal. & Advanc, Techn., 45/2, 239–250, https://doi.org/10.15407/mfint. 45.02.0239.
32.
MARUDA R.W., KROLCZYK G.M., MICHALSKI M., 2017, Structural and Microhardness Changes After Turning of the AISI 1045 Steel for Minimum Quantity Cooling Lubrication, Journal of Materials Engineering and Performance, 26, 431–438.
33.
ROTELLA G., DILLON O.W., UMBRELLO D., SETTINERI L., JAWAHIR I.S., 2014, The Effects of Cooling Conditions on Surface Integrity in Machining of Ti6Al4V Alloy, The International Journal of Advanced Manufacturing Technology, 71, 47–55.
34.
YANG Y., JIN L., ZHU J., 2020, Study on Cutting Force, Cutting Temperature and Machining Residual Stress in Precision Turning of Pure Iron with Different Grain Sizes, Chinese J. of Mechanical Engineering, 33/53, 1–9.
35.
ZHAO G.Y., LIU Z.Y., HE Y., CAO H.J., GUO Y.B., 2017, Energy Consumption in Machining: Classification, Prediction, and Reduction Strategy, Energy, 133, 142–157.
36.
AKHIL C., ANANTHAVISHNU M., AKHIL C., AFEEZ P., AKHILESH R., RAJAN R., 2016, Measurement of Cutting Temperature During Machining, Journal of Mechanical and Civil Engineering, 13/2, 108–122.
37.
STRUZIKIEWICZ G., 2013, Analysis of temperature measurement correctness in cutting zone during 4H13 steel turning, Inzynieria Maszyn, vol 18/4, 72–85, (in Polish).
38.
BRILI N., FICKO M., KLANCNIK S., 2021, Automatic Identification of Tool Wear Based on Thermography and a Convolutional Neural Network During the Turning Process, Sensors, 21/5, 1917, https://doi.org/10.3390/s21051....
39.
KISZKA P., GRZESIK W., RECH J., 2015, Analysis of temperature distribution layout within the cutting zone by means of an infrared camera, Mechanik, 3, 197–200.
40.
BORUI: EN-GJL-250 specification, https://www.iron-foundry.com/e... (available on-line on 26-06-2023).
41.
BASEDOSTEEL:1.4301 specification, https://www.basedosteel.com/en... (available on-line at 26-06-2023).
44.
PALOPOSKI T., LIEDQUIST L., 2005, Steel Emissivity at High Temperatures, Espoo, Publisher VTT Technical Research Centre of Finland.
| eISSN: | 2391-8071 |
| ISSN: | 1895-7595 |
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