Machining and optimization of the external diamond burnishing operation

Nguyen, Trung Thanh; Van, An-Le

doi:10.1080/10426914.2022.2072880

Cited by 6 publications

(7 citation statements)

References 36 publications

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“…The droplets with a small diameter and higher velocity can easily distribute in the working space; hence, the value of the particulate matter index increases. A similar impact of the air pressure on the particulate matter index can be found in the work of [16].…”

Section: Influences Of Mql Variables On the Responsessupporting

confidence: 77%

“…An increased diameter increases the oil quantity of lubricant in the oil mist, which is widely distributed into the air through MQL nozzles; hence, the PI value increases. A similar impact of the nozzle diameter on the particulate matter index can be found in the work of [16].…”

Section: Influences Of Mql Variables On the Responsessupporting

confidence: 76%

“…When the inclined angle increases, a higher proportion of the oil mist evaporates into the surrounding environment, resulting in a higher value of the particulate matter index. A higher PI value with an increased inclined angle can be found in the work of [16].…”

Section: Influences Of Mql Variables On the Responsesmentioning

confidence: 76%

“…A higher oil quantity causes an increment in the amount of oil consumed and the number of oil droplets, which are easily distributed into the air; hence, the PI value increases. A higher PI value with an increased oil quantity is presented in the work of [16].…”

Section: Influences Of Mql Variables On the Responsesmentioning

confidence: 89%

“…The authors stated that EB, mean roughness, and roundness deviation were decreased by 12.2%, 14.2%, and 42.5%, respectively at the optimality. The optimal values of the spraying distance (S), A, P, and F were selected to decrease the carbon emission, particulate matter index (PI), and the maximum roughness of the diamond burnishing process [16]. The author stated that the carbon emission, PI, and roughness were decreased by 3.8%, 26.5%, and 11.6%, respectively.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Influences Of Mql Variables On the Responsessupporting

confidence: 77%

Section: Influences Of Mql Variables On the Responsessupporting

confidence: 76%

Section: Influences Of Mql Variables On the Responsesmentioning

confidence: 76%

Section: Influences Of Mql Variables On the Responsesmentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

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