Multi-performance optimization of multi-roller burnishing process in sustainable lubrication condition

Nguyen, Trung Thanh; Trinh, Quang Hung; Le, Xuan-Ba

doi:10.1080/10426914.2021.1962533

Cited by 10 publications

(5 citation statements)

References 36 publications

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“…The values of the spindle speed and feed rate are determined based on the specifications of the CNC machine. These values [9] [10] [11] [12] [13] are confirmed by the recommendations of the manufacturer of the burnishing tool. The ranges of the depth of penetration are selected using the configuration of the burnishing tool.…”

Section: F(xn)]supporting

confidence: 64%

“…Duncheva et al presented that the fatigue life of the 2024-T3 Al could be improved by more than 2000 times with the support of the single toroidal roller burnishing [10]. The total energy consumption (TE), mean roughness depth (MR), and CC models of the MQL-assisted burnishing operation were proposed in terms of the S, D, flow rate (F), and inlet pressure (P) [11]. The authors stated that TE, MR, and CC were decreased by 12.2%, 14.2%, and 42.5%, respectively at the optimality.…”

Section: Introductionmentioning

confidence: 99%

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Performance optimization of multi-roller flat burnishing process in terms of surface properties

Thai¹,

Van²,

Nguyen³

2023

Journal of Machine Engineering

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In the current investigation, two primary indicators, including the average roughness (AR) and Brinell hardness (BH) of the roller burnishing operation are enhanced using the optimal inputs (the spindle speed-S, feed rate-f, and depth of penetration-D). The performance measures are developed using the Kriging approach and optimal outcomes are generated by the Crow Search Algorithm (CSA). The optimal outcomes generated by the CSA of the S, f, and D were 832 rpm, 112 mm/min, and 0.12 mm, while the AR was reduced by 37.0% and the BH was increased by 29.9%, respectively. The optimal findings could be utilized in the practice for enhancing the burnished quality and to develop a professional system related to the roller burnishing operation. The Kriging-based AR and BH correlations could be used to present nonlinear experimental data. The optimizing technique could be utilized to deal with optimizing problems for different machining operations.

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Section: F(xn)]supporting

confidence: 64%

Section: Introductionmentioning

confidence: 99%

Performance optimization of multi-roller flat burnishing process in terms of surface properties

Thai¹,

Van²,

Nguyen³

2023

Journal of Machine Engineering

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“…The results indicated that the EB and Ra were decreased by 33.0% and 16.0%, respectively. The EB, mean roughness, and roundness models of the MQL-assisted burnishing operation were proposed in terms of the S, f, F, and P [15]. The authors stated that EB, mean roughness, and roundness deviation were decreased by 12.2%, 14.2%, and 42.5%, respectively at the optimality.…”

Section: Introductionmentioning

confidence: 99%

Multi-Response Optimization of Burnishing Variables for Minimizing Environmental Impacts

2023

Teh. vjesn.

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The purpose of this investigation is to optimize minimum quantity lubrication (MQL) variables, including the nozzle diameter (D), inclined angle (A), air pressure (P), oil quantity (F), and spraying distance (S) for decreasing the energy consumption in the burnishing time (EB) and particulate matter index (PI) of the interior burnishing process. The optimal adaptive neuro-based-fuzzy inference system (ANFIS) models of the performance measures were proposed in terms of the MQL variables with the aid of the Taguchi method. The non-dominated sorting genetic algorithm based on the grid partitioning (NSGA-G) and TOPSI were employed to produce feasible solutions and determine the best optimal point. The obtained results indicated that the optimal values of the D, A, P, F, and S are 1.0 mm, 35 deg., 3 Bar, 70 ml/h, and 10 mm, respectively, while the EB and PI are decreased by 8.0% and 15.7% at the optimal solution. The optimal ANFIS models were trustworthy and ensure accurate predictions. The optimization technique comprising the ANFIS, NSGA-G, and TOPSIS could be extensively utilized to determine the optimal outcomes instead of the trial-error and/or human experience. The outcomes could help to decrease environmental impacts in the practical burnishing process.

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“…Nguyen and Le revealed that the energy consumption and Rs of the external burnishing were reduced by 33.0% and 16.0%, respectively [13]. Nguyen et al stated that the total energy, mean roughness, and roundness of the MQL-assisted internal burnishing were reduced by 12.0%, 14.0%, and 43.0%, respectively [14]. The carbon emissions, air pollution, and maximum roughness of the DB process of the carbon steel were decreased by 3.8%, 26.5%, and 34.3% using the optimal factors [15].…”

Section: Introductionmentioning

confidence: 99%

Ecological design optimization of nozzle parameters for burnishing operation

Thai¹,

Van²,

Nguyen³

et al. 2023

J Appl Eng Science

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The design configuration of the nozzle has a vital role in the performance measures of the machining processes. However, parameter optimizations are primary considerations of published works. This study optimizes nozzle design parameters to minimize environmental impacts and enhance the surface quality for the diamond burnishing (DB) operation. The performance measures considered are energy efficiency (ED), noise emission (NE), and the total height of profile roughness (Rt). The variables are the inner diameter (D), spraying distance (S), and pitch angle (P). The optimal Taguchi-based Bayesian regularized feed-forward neural network (TBRFFNN) was applied to propose performance models. The CRITIC approach is utilized to compute the weight values of responses, while the desirability approach (DA) is employed to select optimality. The observed results of the D, S, and P were 3.0 mm, 15 mm, and 45 deg., respectively. The ED was enhanced by 12.7%, while the RT and NE were decreased by 24.4% and 9.1%, respectively, as compared to the original design parameters. The obtained outcomes could be utilized in the practice to boost technical characteristics. The developed optimizing approach could be employed to deal with optimization problems for different machining processes

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Multi-performance optimization of multi-roller burnishing process in sustainable lubrication condition

Cited by 10 publications

References 36 publications

Performance optimization of multi-roller flat burnishing process in terms of surface properties

Performance optimization of multi-roller flat burnishing process in terms of surface properties

Multi-Response Optimization of Burnishing Variables for Minimizing Environmental Impacts

Ecological design optimization of nozzle parameters for burnishing operation

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