Application of a wheel cleaning system during grinding of alumina with minimum quantity lubrication

Lopes, José Cláudio; Ventura, Carlos Eiji Hirata; Fernandes, Lucas de Martini; Tavares, André Bueno; Sanchez, Luiz Eduardo de Ângelo; Mello, Hamilton José de; Aguiar, Paulo; Bianchi, Eduardo Carlos

doi:10.1007/s00170-018-3174-4

Cited by 51 publications

(10 citation statements)

References 23 publications

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“…Such analysis determines the impact of each input unit on the output of the network. Equation (11) will be utilized to assess the sensitivity analysis of diferent input variables ( I i ) on the output of the network [69]: According to equation (11), when the value of a specifc input variable is high, it will make more contributions to the output of the network. Te results of the calculation are depicted in Figure 6.…”

Section: Developed Objective Functionsmentioning

confidence: 99%

“…Some recent works examined adding another auxiliary nozzle in the grinding zone in order to improve efficiency. With this regard, using four compressed air nozzle jets at various angles, comprising 0, 30, 60, and 90 de grees, was conducted by Lopes et al They found that employing flood coolant, followed by minimum quantity lubrication (MQL) with a compressed air jet at a 30 de grees angle to the wheel surface, is the most efficient method for cleaning the grinding wheel, lowering diametrical wheel wear, and surface roughness [ 11 ]. In the following, Hatami Farzaneh et al used an auxiliary compressed air jet system to investigate the effect of the incidence angle at various angles to clean the wheel surface and reduce wheel loading.…”

Section: Introductionmentioning

confidence: 99%

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Optimization of Grinding Parameters of Tool Steel by the Soft Computing Technique

Hatami

Sayadi

Razbin

et al. 2022

Computational Intelligence and Neuroscience

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Grinding is one of the most complex and accurate machining processes, and the efficiency of the grinding wheel depends significantly on its surface properties. This work aims to propose an algorithmic manner that reduces the cost and time to conduct grinding of an optimized DIN 1.2080 tool steel (SPK) using a soft computing technique to obtain the best combination of input parameters including depth of cut (20, 40, 60 μ m ), wheel speed (15, 20, 25 m / s ), feed rate (100, 300, 500 m m / s ), and incidence angle (0, 30, 45 d e g r e e s ) with respect to output parameters consisting of average surface roughness and specific grinding energy. According to the input parameters and their levels, an experiment using fractional factorial design of experiment (RFDOE) was designed. Later on, two parallel feed-forward backpropagation (FFBPNN) networks with similar topology made up of 4, 11, and 1 units in their input, hidden, and output layers are trained, respectively. After sensitivity analyses of networks for determination of the relative importance of input variables, a genetic algorithm (GA) adopting linear programming (LP) based on Euclidean distance is coupled to networks to seek out the best combinations of input parameters that result in minimum average surface roughness and minimum specific grinding energy. The findings revealed that RFDOE provides valid data for training FFBP networks with a total goodness value of more than 1.99 in both cases. The sensitivity analyses showed that feed rate (38.97%) and incidence angle (33.94%) contribute the most in the case of average surface roughness and specific grinding energy networks, respectively. Despite the similar surface quality based on scanning electron microscopy (SEM), the optimization resulted in an optimized condition of the depth of cut of 25.23 μ m , wheel speed of 15.02 m m / s , feed rate of 369.45 m m / s , and incidence angle of 44.98 d e g r e e s , which had a lower cost value (0.0146) than the optimum one (0.0953). Thus, this study highlights that RFDOE with a hybrid optimization using FFBP networks-GA/LP can effectively minimize both average surface roughness and specific grinding energy of SPK.

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Section: Developed Objective Functionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization of Grinding Parameters of Tool Steel by the Soft Computing Technique

Hatami

Sayadi

Razbin

et al. 2022

Computational Intelligence and Neuroscience

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“…The study revealed that the addition of 0.2 wt% of diamond nanoparticles to PAO synthetic oil was able to substantially reduce coefficient of friction and adhesion wear on machining tools due to the reduction of sliding contacts between tool–workpiece interface and smoothening of sharp asperities. In another study by Lopes et al [ 148 ] on the application of wheel cleaning system during alumina grinding under semi-synthetic oil MQL delivered through air jet showed that flooded machining provided the optimal experimental results. However, the delivery of the semi-synthetic oil under MQL at air jet angle of 30° showed similar results to flooded cooling, with the increase of grinding wheel diameter by 83% and improvement of surface roughness and power consumption by 53% and 22% respectively.…”

Section: Types Of Cutting Fluidsmentioning

confidence: 99%

Recent progress and evolution of coolant usages in conventional machining methods: a comprehensive review

Kui

Islam

Reddy

et al. 2021

Int J Adv Manuf Technol

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This paper reviews recent progress and applications of usage of cutting fluids in conventional machining processes. In addition to reviewing the various conventional and advanced cooling techniques during machining, the paper also discusses the use of minimum quantity lubrication (MQL) in several types on metals such as steel, aluminum, alloy, and titanium alloys. Due to the toxicity of conventional cutting fluid resulting in ecological problems, the demand for environmentally friendly cutting fluid is rising. Therefore, natural vegetable oil is chosen as potential replacement as an environmentally friendly cutting fluid which fulfills the important aspects of biodegradability and sustainability. Application of vegetable oil-based cutting fluids under MQL techniques are also discussed. Moreover, the potential of palm oil as biodegradable and environmentally friendly natural vegetable oil-based metal-working fluids in MQL are reviewed.

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“…In the horizontal position and nozzle angle of 30°, the situation was worsened. This can be attributed to the chips clogged on the surface of the wheel which cannot be removed by the cleaning nozzle [18]. In these two cases, the air nozzle helps the chips to adhere and get stuck on the pores of the grinding wheel, increasing both loading and forces [19].…”

Section: Surface Roughnessmentioning

confidence: 99%

Application of an Auxiliary Wheel Cleaning System in the Grinding of SPK Tool Steel

Adibi

Hatami

Rezaei

2021

Preprint

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Grinding operation is one of the most complex and accurate machining processes whose performance is highly dependent on the surface conditions of the grinding wheel. As the friction between abrasive grains and the workpiece results in a large amount of heat, the use of coolant can prevent the workpiece surface from burning, microstructure alteration, subsurface damages, and hardness variation. To get better the cleaning of the abrasive grains on the surface of the wheel during the grinding process, this paper is focused on the performance of an auxiliary compressed air jet system during grinding of hard-to-grind materials. Moreover, the wheel loading of the grinding wheel will also be evaluated. Different incident angles of the compressed air nozzle (0˚, 30˚, 45˚, and 60˚) were examined. Furthermore, conventional flood coolant, as well as drying with and without a cleaning system, was applied for comparison purposes. Surface roughness, tangential forces, specific energy, wheel loading analysis, and SEM images were evaluated where the incident angle of 45˚ led to the best results. Wheel loading resulted in the accumulation of chips between abrasive grains to the top of cutting grains. Detection and identification of loading has been operated based on image processing technique.

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Application of a wheel cleaning system during grinding of alumina with minimum quantity lubrication

Cited by 51 publications

References 23 publications

Optimization of Grinding Parameters of Tool Steel by the Soft Computing Technique

Optimization of Grinding Parameters of Tool Steel by the Soft Computing Technique

Recent progress and evolution of coolant usages in conventional machining methods: a comprehensive review

Application of an Auxiliary Wheel Cleaning System in the Grinding of SPK Tool Steel

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