Parametric Optimization for Cutting Forces and Material Removal Rate in the Turning of AISI 5140

Kuntoğlu, Mustafa; Acar, Osman; Gupta, Munish Kumar; Sağlam, Hacı; Sarıkaya, Murat; Giasin, Khaled; Pimenov, Danil Yurievich

doi:10.3390/machines9050090

Cited by 34 publications

(18 citation statements)

References 54 publications

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“…In an abrasive waterjet, cutting is generated by material removal caused by abrasive particles that hit the workpiece at high velocity and are influenced by the thickness and hardness of the target material [12]. Fundamentally, the productivity performance of AWJM is indicated by the removed material per unit of time [13]. In addition, surface roughness is the primary indicator of surface quality level which defines the scale of smoothness of the machined parts [14].…”

Section: Introductionmentioning

confidence: 99%

Analysis and Optimization of Process Parameters in Abrasive Waterjet Contour Cutting of AISI 304L

Llanto

Vafadar

Aamir

et al. 2021

Metals

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Abrasive waterjet machining is applied in various industries for contour cutting of heat-sensitive and difficult-to-cut materials like austenitic stainless steel 304L, with the goal of ensuring high surface integrity and efficiency. In alignment with this manufacturing aspiration, experimental analysis and optimization were carried out on abrasive waterjet machining of austenitic stainless steel 304L with the objectives of minimizing surface roughness and maximizing material removal rate. In this machining process, process parameters are critical factors influencing contour cutting performance. Accordingly, Taguchi’s S/N ratio method has been used in this study for the optimization of process parameters. Further in this work, the impacts of input parameters are investigated, including waterjet pressure, abrasive mass flow rate, traverse speed and material thickness on material removal rate and surface roughness. The study reveals that an increasing level of waterjet pressure and abrasive mass flow rate achieved better surface integrity and higher material removal values. The average S/N ratio results indicate an optimum value of waterjet pressure at 300 MPa and abrasive mass flow rate of 500 g/min achieved minimum surface roughness and maximum material removal rate. It was also found that an optimized value of a traverse speed at 90 mm/min generates the lowest surface roughness and 150 mm/min produces the highest rate of material removed. Moreover, analysis of variance in the study showed that material thickness was the most influencing parameter on surface roughness and material removal rate, with a percentage contribution ranging 90.72–97.74% and 65.55–78.17%, respectively.

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Section: Introductionmentioning

confidence: 99%

Analysis and Optimization of Process Parameters in Abrasive Waterjet Contour Cutting of AISI 304L

Llanto

Vafadar

Aamir

et al. 2021

Metals

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“…As is known, the Taguchi approach uses objective functions in order to optimize the related response parameter. For this, three equations are used, namely maximization, minimization, and normalization equations [34][35][36]. Since the power, temperature, and wear parameters should ideally be minimal, the second equation is used.…”

Section: Experimental Design Optimization Approach and Statistical Analysismentioning

confidence: 99%

The Effects of MQL and Dry Environments on Tool Wear, Cutting Temperature, and Power Consumption during End Milling of AISI 1040 Steel

Salur

Kuntoğlu

Aslan

et al. 2021

Metals

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Minimum quantity lubrication (MQL) is a sustainable method that has been efficiently applied to achieve machinability improvements with various materials in recent years, such as hardened steels, superalloys, soft metals, and composites. This study is the first to focus on the performance evaluation of MQL and dry milling environments with AISI 1040 steel. The tool wear, cutting temperature, and power consumption were considered as the quality responses while cutting speed, feed rate and machining environment are taken as input parameters. The effects of the influential factors are analyzed using analysis of variance (ANOVA) and bar charts. Additionally, Taguchi signal-to-noise (S/N) ratios are utilized in order to determine the optimum parameters for the best quality responses. The results show that the MQL system provides better performance compared to dry milling by reducing the tool wear, cutting temperature, and power consumption. According to the ANOVA results, the cutting environment affects the cutting temperature (37%) and power consumption (94%), while cutting speed has importance effects on the tool wear (74%). A lower cutting speed (100 m/min) and feed rate (0.10 mm/rev) should be selected under MQL conditions to ensure minimum tool wear and power consumption; however, a higher feed rate (0.15 mm/rev) needs to be selected along with a low cutting speed and MQL conditions to ensure better temperatures. A comparative evaluation is carried out on the tool wear, cutting temperature, and power consumption under MQL and dry environments. This investigation is expected to contribute to the current literature, highlighting the superiority of sustainable methods in the milling of industrially important materials.

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“…Accurate real-time monitoring of cutting force is helpful to study the mechanism of the cutting process and effectively control machining quality and tool life. Therefore, many researchers have done a lot of work on cutting force [1][2][3][4][5][6]. Cutting force dynamometers include strain dynamometers, piezoelectric dynamometers, current dynamometers, capacitive and hydraulic dynamometers.…”

Section: Introductionmentioning

confidence: 99%

Fabrication, Performance, Characterization and Experimental Calibration of Embedded Thin-Film Sensor for Tool Cutting Force Measurement

Cheng

Liu

et al. 2022

Micromachines

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Thin-film strain sensors are widely used because of their small volume, fast strain response and high measurement accuracy. Among them, the thin-film material and preparation process of thin-film strain sensors for force measurement are important aspects. In this paper, the preparation process parameters of the transition layer, insulating layer and Ni-Cr alloy layer in a thin-film strain sensor are analyzed and optimized, and the influence of each process parameter on the properties of the thin film are discussed. The surface microstructure of the insulating layer with Al2O3 or Si3N4 transition layers and the film without transition layer were observed by atomic force microscopy. It is analyzed that adding a transition layer between the stainless steel substrate and insulation layer can improve the adhesion and flatness of the insulation layer. The effects of process parameters on elastic modulus, nanohardness and strain sensitivity coefficient of the Ni-Cr resistance layer are discussed, and electrical parameters such as the resistance strain coefficient are analyzed and characterized. The static calibration of the thin-film strain sensor is carried out, and the relationship between the strain value and the output voltage is obtained. The results show that the thin-film strain sensor can obtain the strain generated by the cutting tool and transform it into an electrical signal with good linearity through the bridge, accurately measuring the cutting force.

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Parametric Optimization for Cutting Forces and Material Removal Rate in the Turning of AISI 5140

Cited by 34 publications

References 54 publications

Analysis and Optimization of Process Parameters in Abrasive Waterjet Contour Cutting of AISI 304L

Analysis and Optimization of Process Parameters in Abrasive Waterjet Contour Cutting of AISI 304L

The Effects of MQL and Dry Environments on Tool Wear, Cutting Temperature, and Power Consumption during End Milling of AISI 1040 Steel

Fabrication, Performance, Characterization and Experimental Calibration of Embedded Thin-Film Sensor for Tool Cutting Force Measurement

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