Turning of hardened AISI H13 steel with recently developed S3P-AlTiSiN coated carbide tool using MWCNT mixed nanofluid under minimum quantity lubrication

Mahapatra, Sitesh; Das, Anshuman; Jena, Pankaj Charan; Das, Sudhansu Ranjan

doi:10.1177/09544062221126357

Cited by 40 publications

(10 citation statements)

References 83 publications

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“…Surface roughness parameters start slightly increasing the cutting speed beyond 190 m/min due to the worn cutting insert. Two major factors (lateral side flow arising from plastic deformation of machined surface and chatter due to vibration) influenced the roughness at a high level of cutting speed (247 m/min), as reported by Mahapatra et al [ 42 ]. In the case of increasing feed rate on all surfaces, roughness variables start increasing and attain high values at a feed of 0.28 mm/rev.…”

Section: Resultsmentioning

confidence: 88%

Investigation on the Performance of Coated Carbide Tool during Dry Turning of AISI 4340 Alloy Steel

et al. 2023

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The machinability of materials is highly affected by their hardness, and it affects power consumption, cutting tool life as well as surface quality while machining the component. This work deals with machining of annealed AISI 4340 alloy steel using a coated carbide tool under a dry environment. The microhardness of annealed and non-annealed workpieces was compared and a significant reduction was found in the microhardness of annealed samples. Microstructure examination of the annealed sample revealed the formation of coarse pearlite which indicated a reduction of hardness and improved ductility. A commercially CVD multilayer (TiN/TiCN/Al2O3/ZrCN) coated cemented carbide cutting tool was employed for turning quenched and tempered structural AISI 4340 alloy steel by varying machining speed, rate of feed, and depth of cut to evaluate the surface quality, machining forces, flank wear, and chip morphology. According to the findings of experiments, the feed rate possesses a high impact on surface finish, followed by cutting speed. The prominent shape of the serrated saw tooth chip was noticed at a higher cutting speed. Machined surface finish and cutting forces during turning is a function of the wear profile of the coated carbide insert. This study proves that annealing is a low-cost and economical process to enhance the machinability of alloy steel.

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Section: Resultsmentioning

confidence: 88%

Investigation on the Performance of Coated Carbide Tool during Dry Turning of AISI 4340 Alloy Steel

et al. 2023

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“…Te CF was increased when tool wear also increased. Te CF produced during the metal cutting impacted the heat generation in the cutting zone, tool wear, machined surface quality, and workpiece accuracy [27,41].…”

Section: Input and Output Parametersmentioning

confidence: 99%

“…Te tool vibration, Ra, and chip morphology was analyzed during the hard turning of hot work AISI H13 steel under multiwalled carbon nanotubes (MWCNTs) mixed nanofuid with MQL condition. Tey observed segmented-type serrated saw-toothed chip morphology and increased fank wear and tool vibration responsible for machined surface fnish degradation [27]. Te experimental investigation was carried out using Taguchi's L 27 orthogonal array.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Flank Wear during Turning of EN8 Steel with Cutting Force Signals Using a Deep Learning Approach

Thangarasu¹,

Mohanraj

Devendran³

et al. 2023

Mathematical Problems in Engineering

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Currently, manufacturing industries focus on intelligent manufacturing. Prediction and monitoring of tool wear are essential in any material removal process, and implementation of a tool condition monitoring system (TCMS) is necessary. This work presents the flank wear prediction during the hard turning of EN8 steel using the deep learning (DL) algorithm. The turning operation is conducted with three levels of selected parameters. CNMG 120408 grade, TiN-coated cemented carbide tool is used for turning. Cutting force and flank wear are assessed under dry-cutting conditions. DL algorithms such as adaptive neuro-fuzzy inference system (ANFIS) and convolutional auto encoder (CAE) are used to predict the flank wear of the single-point cutting tool. The DL model is developed with turning parameters and cutting force to predict flank wear. The different ANFIS and CAE models are employed to develop the prediction model. Grid-based ANFIS structure with Gauss membership function performed better than ANFIS models. The ANFIS model’s average testing error of 0.0074011 mm and prediction accuracy of 99.81% are achieved.

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“…Moreover, MQL applied with compressed air encourages faster heat dissipation and chip removal during machining. Another study conducted by Mahapatra et al (2023) evaluated the machining performance of hardened steel grade H13 using multiwalled carbon nanotube (MWCNT)-based nanofluid and noticed a significant reduction of chip thickness under the MQL system. Sahu et al (2018) examined 0.2% vol.…”

Section: Minimum Quantity Lubrication Turning Under Mono Nanofluidsmentioning

confidence: 99%

A review on minimum quantity lubrication (MQL) assisted machining processes using mono and hybrid nanofluids

Singh,

Singh

2023

ILT

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Purpose Because many cutting fluids contain hazardous chemical constituents, industries and researchers are looking for alternative methods to reduce the consumption of cutting fluids in machining operations due to growing awareness of ecological and health issues, government strict environmental regulations and economic pressures. Therefore, the purpose of this study is to raise awareness of the minimum quantity lubrication (MQL) technique as a potential substitute for environmental restricted wet (flooded) machining situations. Design/methodology/approach The methodology adopted for conducting a review in this study includes four sections: establishment of MQL technique and review of MQL machining performance comparison with dry and wet (flooded) environments; analysis of the past literature to examine MQL turning performance under mono nanofluids (M-NF); MQL turning performance evaluation under hybrid nanofluids (H-NF); and MQL milling, drilling and grinding performance assessment under M-NF and H-NF. Findings From the extensive review, it has been found that MQL results in lower cutting zone temperature, reduction in cutting forces, enhanced tool life and better machined surface quality compared to dry and wet cutting conditions. Also, MQL under H-NF discloses notably improved tribo-performance due to the synergistic effect caused by the physical encapsulation of spherical nanoparticles between the nanosheets of lamellar structured nanoparticles when compared with M-NF. The findings of this study recommend that MQL with nanofluids can replace dry and flood lubrication conditions for superior machining performance. Practical implications Machining under the MQL regime provides a dry, clean, healthy and pollution-free working area, thereby resulting the machining of materials green and environmentally friendly. Originality/value This paper describes the suitability of MQL for different machining operations using M-NF and H-NF. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0131/

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Turning of hardened AISI H13 steel with recently developed S3P-AlTiSiN coated carbide tool using MWCNT mixed nanofluid under minimum quantity lubrication

Cited by 40 publications

References 83 publications

Investigation on the Performance of Coated Carbide Tool during Dry Turning of AISI 4340 Alloy Steel

Investigation on the Performance of Coated Carbide Tool during Dry Turning of AISI 4340 Alloy Steel

Prediction of Flank Wear during Turning of EN8 Steel with Cutting Force Signals Using a Deep Learning Approach

A review on minimum quantity lubrication (MQL) assisted machining processes using mono and hybrid nanofluids

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