Comparative Studies on Machinability of MCLA Steels EN19 and EN24 Using Taguchi Optimization Techniques

Geethanjali, K.S.; Ramesha, C; Chandan, B.R.

doi:10.1016/j.matpr.2018.11.012

Cited by 7 publications

(5 citation statements)

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“…AISI-4140 alloy steel is a typical 1% chromium molybdenum steel with higher molybdenum and comes under the category of high-quality medium carbon structural steel [13]. In the current experimental work, specimens are prepared using untreated AISI-4140 alloy steel that is well known to possess high tensile strength and shock resistance properties.…”

Section: Methodsmentioning

confidence: 99%

Investigation of Plane-Strain Fracture Toughness and Failure Analysis of AISI-4140 Alloy Steel

Upadhyaya,

Kottawar,

Patil

et al. 2023

RAiSE-2023

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Section: Methodsmentioning

confidence: 99%

Investigation of Plane-Strain Fracture Toughness and Failure Analysis of AISI-4140 Alloy Steel

Upadhyaya,

Kottawar,

Patil

et al. 2023

RAiSE-2023

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“…The workpiece was a 709M40 alloy steel bars, which were around 410 mm long with a diameter of 100 mm. The workpiece is often supplied in the hardened and tempered condition with a tensile strength ranging from 850–1000

due to its good ductility and shock resistance and resistance to wear properties [ 26 ]. The treatment condition used for the workpiece was soft annealed.…”

Section: Methodsmentioning

confidence: 99%

Estimation and Optimization of Tool Wear in Conventional Turning of 709M40 Alloy Steel Using Support Vector Machine (SVM) with Bayesian Optimization

Alajmi

Almeshal

2021

Materials

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Cutting tool wear reduces the quality of the product in production processes. The optimization of both the machining parameters and tool life reliability is an increasing research trend to save manufacturing resources. In the present work, we introduced a computational approach in estimating the tool wear in the turning process using artificial intelligence. Support vector machines (SVM) for regression with Bayesian optimization is used to determine the tool wear based on various machining parameters. A coated insert carbide tool 2025 was utilized in turning tests of 709M40 alloy steel. Experimental data were collected for three machining parameters like feed rate, depth of cut, and cutting speed, while the parameter of tool wear was calculated with a scanning electron microscope (SEM). The SVM model was trained on 162 experimental data points and the trained model was then used to estimate the experimental testing data points to determine the model performance. The proposed SVM model with Bayesian optimization achieved a superior accuracy in estimation of the tool wear with a mean absolute percentage error (MAPE) of 6.13% and root mean square error (RMSE) of 2.29%. The results suggest the feasibility of adopting artificial intelligence methods in estimating the machining parameters to reduce the time and costs of manufacturing processes and contribute toward greater sustainability.

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“…Adequate care is taken to forge the components within the prescribed temperature range of 850-1100 0 C. MCLA steels, viz., EN18 and EN19 were forged in the Vishnu Forging Industries Ltd, Bangalore. Figure 1 shows the forging procedure of selected steels by power hammer in forging shop [14,15].…”

Section: Forgingmentioning

confidence: 99%

Effect of Polymer Quenchants on the Toughness and Hardness of Different Medium Carbon Low Alloy Steels.

Ramesha,

B R,

K N

et al. 2023

jmmf

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In the present study, medium carbon low alloy (MCLA) steels like AISI 5140 (EN18) and AISI 4140 (EN19) are treated in different quenching media under solutionizing temperature of 855°C. Quenched in SAE 250 oil, polyethylene glycol (PEG) (10% and 30%), and water. The quenched samples are step-tempered at 575°C and at 220°C sequentially with 60 minute soaking time. BHN, YS, UTS and tensile toughness are determined for the untreated and heat-treated samples. It is found that there is an excellent correlation, with correlation coefficients of 0.97. The standard generalized equation for these two steels are established. Tensile toughness = 19000 + 12 BHN- 215 El. The study revealed that the PEG is better in terms of cost, fire-resistant and biodegradable. 30% polymer quenched samples result in better tensile toughness properties as compared to 10% polymer quenched samples.

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Comparative Studies on Machinability of MCLA Steels EN19 and EN24 Using Taguchi Optimization Techniques

Cited by 7 publications

References 0 publications

Investigation of Plane-Strain Fracture Toughness and Failure Analysis of AISI-4140 Alloy Steel

Investigation of Plane-Strain Fracture Toughness and Failure Analysis of AISI-4140 Alloy Steel

Estimation and Optimization of Tool Wear in Conventional Turning of 709M40 Alloy Steel Using Support Vector Machine (SVM) with Bayesian Optimization

Effect of Polymer Quenchants on the Toughness and Hardness of Different Medium Carbon Low Alloy Steels.

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