Optimization of energy consumption response parameters for turning operation using Taguchi method

Bilga, Paramjit Singh; Singh, Sehijpal; Kumar, Raman

doi:10.1016/j.jclepro.2016.07.220

Cited by 152 publications

(39 citation statements)

References 33 publications

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“…Taguchi method proposed that the signal to noise ratio (S/N) can be used to measure the quality characteristic deviates from the desired value [35][36]. These quality characteristics are defined for the stable dispersions as smaller the better (average particle size), the higher the better that should be maximized (electrical conductivity) or the nominal the better that should be kept a target value [37]. The variability degree of factors' effect on the quality characteristics could be analyzed efficiently by the regression analysis [38].…”

Section: A General Outlook On the Issue Of Topsis Based Taguchi Optimmentioning

confidence: 99%

Improvement of the Graphene Oxide Dispersion Properties with the Use of TOPSIS Based Taguchi Application

Şimşek

Ultav

Korucu

et al. 2018

Period. Polytech. Chem. Eng.

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[20]. In many industrial applications, the stability of graphene oxide dispersions plays a crucial role for the proper solvent preparation. Therefore, many researchers have done the studies to understand the dispersion behavior and to improve the dispersion stability. Konios et al. [21] prepared GO and reduced graphene oxide (rGO) dispersions with the different solvents and they showed that the GO and rGO samples forms a stable dispersion with the deionized-water, ethylene glycol and N-methyl-2-pyrrolidone (NMP). Taha-Tijerina et al. [22] prepared a dispersion with the deionized-water, ethylene glycol, ethanol and mineral oil and they illustrated that the GO samples forms a strong stable dispersion with the deionized-water and ethylene glycol. Graphene oxide-deionized water nano-fluids are more attractive options because of the formation of fairly strong stable dispersions with graphene oxide in the deionized water and the elimination of toxic solvents such as NMP.The quality of the dispersions including "strong stability" can be represented with some criteria such as zeta potential value, thermal and electrical conductivity, pH, and particle size. Therefore, many studies have been done to analyze the GO dispersion properties. The average particle size and zeta potential value [22] [29] were analyzed without using any systematic analyzing such an experimental design approach. It has been determined that oxidants and pH of the

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Section: A General Outlook On the Issue Of Topsis Based Taguchi Optimmentioning

confidence: 99%

Improvement of the Graphene Oxide Dispersion Properties with the Use of TOPSIS Based Taguchi Application

Şimşek

Ultav

Korucu

et al. 2018

Period. Polytech. Chem. Eng.

View full text Add to dashboard Cite

show abstract

“…Conventional experimental methods require a large number of experiments, leading to a waste of resources. Taguchi's method can solve this problem well, as it can minimize variation around a target value [19,20], and offers the opportunity to increase efficiency by optimizing the machining parameters with fewer experiments [21][22][23][24]. Taguchi's method analyzes a result through the signal-to-noise ratio (S/N ratio), by creating a number of orthogonal arrays in the design of experiment (DOE).…”

Section: Taguchi Methodsmentioning

confidence: 99%

Surface Quality Improvement in Machining an Aluminum Honeycomb by Ice Fixation

Wang

Gan

et al. 2020

Chin. J. Mech. Eng.

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A honeycomb structure is widely used in sandwich structure components in aeronautics and astronautics; however, machining is required to reveal some of its features. In honeycomb structures, deficiencies, such as burrs, edge subsiding, and cracking, can easily appear, owing to poor specific stiffness in the radial direction. Some effective fixation methods based on a filling principle have been applied by researchers, including approaches based on wax, polyethylene glycol, iron powder, and (especially) ice. However, few studies have addressed the optimization of the cutting parameters. This study focused on optimizing the cutting parameters to obtain a better surface roughness (calculated as a roughness average or R a ) and surface morphology in the machining of an aluminum alloy honeycomb by an ice fixation method. A Taguchi method and an analysis of variance were used to analyze the effects and contributions of spindle speed, cutting depth, and feed rate. The optimal cutting parameters were determined using the signal-to-noise ratio combined with the surface morphology. An F-value and P-value were calculated for the value of the R a , according to a "smaller is better" model. Additionally, the optimum cutting parameters for machining the aluminum honeycomb by ice fixation were found at different levels. The results of this study showed that the optimal parameters were a feed rate of 50 mm/min, cutting depth of 1.2 mm, and spindle speed of 4000 r/min. Feed rate was the most significant factor for minimizing R a and improving the surface morphology, followed by spindle speed. The cutting depth had little effect on R a and surface morphology. After optimization, the value of R a could reach 0.218 μm, and no surface morphology deterioration was observed in the verified experiment. Thus, this research proposes optimal parameters based on ice fixation for improving the surface quality.

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“…Zhong et al [10] considered the effects of the cutting parameter combinations on the energy consumption at a certain material removal rate, and based on this discovery, considered a specific energy consumption as the optimization goal and took the cutting parameters as the optimization variables during the material removal process during the turning; cutting parameter sets with a large feed rate were then recommended. Bilga et al [11] regarded the cutting speed, feed rate, cutting depth, and nose radius along with their interactions as the variables to optimize energy consumption, and showed that the feed rate is the vital dominating parameter for a reduction of the energy consumed; however, the nose radius does not contribute much. To lower the specific cutting energy in high-speed milling, Wang et al [12] took 7050-T7451 aluminum alloy as the processing object to reveal the influence of the cutting speed, undeformed chip thickness, and tool rake angle on the cutting energy consumption.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Cutting Parameters for Trade-off Among Carbon Emissions, Surface Roughness, and Processing Time

Jiang

Gao

Lü

et al. 2019

Chin. J. Mech. Eng.

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As the manufacturing industry is facing increasingly serious environmental problems, because of which carbon tax policies are being implemented, choosing the optimum cutting parameters during the machining process is crucial for automobile panel dies in order to achieve synergistic minimization of the environment impact, product quality, and processing efficiency. This paper presents a processing task-based evaluation method to optimize the cutting parameters, considering the trade-off among carbon emissions, surface roughness, and processing time. Three objective models and their relationships with the cutting parameters were obtained through input-output, response surface, and theoretical analyses, respectively. Examples of cylindrical turning were applied to achieve a central composite design (CCD), and relative validation experiments were applied to evaluate the proposed method. The experiments were conducted on the CAK50135di lathe cutting of AISI 1045 steel, and NSGA-II was used to obtain the Pareto fronts of the three objectives. Based on the TOPSIS method, the Pareto solution set was ranked to find the optimal solution to evaluate and select the optimal cutting parameters. An S/N ratio analysis and contour plots were applied to analyze the influence of each decision variable on the optimization objective. Finally, the changing rules of a single factor for each objective were analyzed. The results demonstrate that the proposed method is effective in finding the trade-off among the three objectives and obtaining reasonable application ranges of the cutting parameters from Pareto fronts.

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Optimization of energy consumption response parameters for turning operation using Taguchi method

Cited by 152 publications

References 33 publications

Improvement of the Graphene Oxide Dispersion Properties with the Use of TOPSIS Based Taguchi Application

Improvement of the Graphene Oxide Dispersion Properties with the Use of TOPSIS Based Taguchi Application

Surface Quality Improvement in Machining an Aluminum Honeycomb by Ice Fixation

Optimization of Cutting Parameters for Trade-off Among Carbon Emissions, Surface Roughness, and Processing Time

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