Sustainability-Based Optimization of the Rotary Turning of the Hardened Steel

Nguyen, Trung-Thanh; Duong, Quoc-Dung; Mia, Mozammel

doi:10.3390/met10070939

Cited by 15 publications

(10 citation statements)

References 26 publications

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“…In this work, ten maximum values of the active turning-burnishing power and machine power consumed are taken into account to calculate the average outcomes. The similar definitions are computed in the works of References [22,23].…”

Section: Optimization Issuesmentioning

confidence: 99%

Modeling and Evaluation of Energy Efficiency of New Hybrid Turning-Burnishing Process in Terms of Surface Properties

Nguyen

Mia

2020

Energies

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The combination of the turning and burnishing process is an efficient approach to improve machined quality and productivity. This paper aims to optimize energy efficiency (EF), improved hardness ratio (IHR), and decreased roughness ratio (DRR) of a new hybrid turning-burnishing process. The machining parameters are the feed rate (f), turning speed (v), depth of cut (a), burnishing pressure (p), and the diameter of the compressing ball (d). A new turning-burnishing tool using compressed air has been designed and fabricated. A set of experiments for Aluminum Alloy 5083 were performed using the Taguchi method. The weightage principal component analysis (WPCA) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were applied to obtain the weight values and optimal outcomes. The results indicated that optimum values of the depth of cut, pressure, diameter, feed rate, and speed are 1.00 mm, 0.4 MPa, 16.00 mm, 0.084 mm/rev, and 120 m/min, respectively. The improvements in the EF and IHR are by 20.75% and 8.23% respectively, while the DDR is decreased by 19.05%, as compared to common values.

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Section: Optimization Issuesmentioning

confidence: 99%

Modeling and Evaluation of Energy Efficiency of New Hybrid Turning-Burnishing Process in Terms of Surface Properties

Nguyen

Mia

2020

Energies

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“…Cutting velocity, feed rate, tool inclination angle, and depth of cut were considered as input variables. Nguyen et al [30] developed a sustainability-based optimization model for the turning process of hardened steel using rotary tools. The genetic algorithm was used, aiming to reduce the machining cost and surface roughness, as well as enhance energy efficiency and operation safety.…”

Section: Property Materialsmentioning

confidence: 99%

Analysis and Optimization of Machining Hardened Steel AISI 4140 with Self-Propelled Rotary Tools

et al. 2021

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It is necessary to improve the machinability of difficult-to-cut materials such as hardened steel, nickel-based alloys, and titanium alloys as these materials offer superior properties such as chemical stability, corrosion resistance, and high strength to weight ratio, making them indispensable for many applications. Machining with self-propelled rotary tools (SPRT) is considered one of the promising techniques used to provide proper tool life even under dry conditions. In this work, an attempt has been performed to analyze, model, and optimize the machining process of AISI 4140 hardened steel using self-propelled rotary tools. Experimental analysis has been offered to (a) compare the fixed and rotary tools performance and (b) study the effect of the inclination angle on the surface quality and tool wear. Moreover, the current study implemented some artificial intelligence-based approaches (i.e., genetic programming and NSGA-II) to model and optimize the machining process of AISI 4140 hardened steel with self-propelled rotary tools. The feed rate, cutting velocity, and inclination angle were the selected design variables, while the tool wear, surface roughness, and material removal rate (MRR) were the studied outputs. The optimal surface roughness was obtained at a cutting speed of 240 m/min, an inclination angle of 20°, and a feed rate of 0.1 mm/rev. In addition, the minimum flank tool wear was observed at a cutting speed of 70 m/min, an inclination angle of 10°, and a feed rate of 0.15 mm/rev. Moreover, different weights have been assigned for the three studied outputs to offer different optimized solutions based on the designer’s interest (equal-weighted, finishing, and productivity scenarios). It should be stated that the findings of the current work offer valuable recommendations to select the optimized cutting conditions when machining hardened steel AISI 4140 within the selected ranges.

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“…The authors stated that energy consumption and roughness were decreased by 50.3% and 19.8%, respectively, while the material removal rate was increased by 33.2%. The energy efficiency, machining costs, and average roughness for the SPRT process were analyzed by Nguyen et al 12 As a result, the energy efficiency was enhanced by 8.9%, while the roughness and cost were reduced by 20.0% and 14.8%, respectively at the optimal solution.…”

Section: Introductionmentioning

confidence: 99%

Multi-response optimization of the actively driven rotary turning for energy efficiency, carbon emissions, and machining quality

Nguyen

Duong

Mia

2021

Proceedings of the Institution of Mechanical Engineers, Part B:

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Boosting energy efficiency and machining quality are prominent solutions to achieve sustainable production for turning operations. In this work, a machining condition-based optimization has been performed to decrease the total specific energy (SEC), carbon emission (CE), and average roughness (AR) of the actively driven rotary turning (ADRT) process. The processing factors are the tool rotational speed (Tv), depth of cut (a), feed rate (fr), and workpiece speed (Wv). The turning experiments of the mold material labeled SKD11 have been conducted on a CNC lathe. The regression method is employed to develop comprehensive models of the total specific energy, carbon emissions, and average roughness. The entropy approach is then applied to drive out the weight value of each ADRT response. Finally, the non-dominated sorting particle swarm optimization (NSPSO) is utilized to determine the optimal parameters. The findings indicated that the optimal values of the Tv, a, fr, and Wv are 77 m/min, 0.32 mm, 0.25 mm/rev., and 128 m/min, respectively. The SEC, AR, and CE are decreased by 18.07%, 10.46%, and 5.02%, respectively, as compared to the initial approach. Moreover, the developed active rotary turning operation can be considered as an effective technical solution to boost the machining efficiency of hardened steels.

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Sustainability-Based Optimization of the Rotary Turning of the Hardened Steel

Cited by 15 publications

References 26 publications

Modeling and Evaluation of Energy Efficiency of New Hybrid Turning-Burnishing Process in Terms of Surface Properties

Modeling and Evaluation of Energy Efficiency of New Hybrid Turning-Burnishing Process in Terms of Surface Properties

Analysis and Optimization of Machining Hardened Steel AISI 4140 with Self-Propelled Rotary Tools

Multi-response optimization of the actively driven rotary turning for energy efficiency, carbon emissions, and machining quality

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