PECVD process parameter optimization: towards increased hardness of diamond-like carbon thin films

Ghadai, Ranjan Kumar; Kalita, Kanak; Mondal, Sankar Prasad; Swain, Bibhu P.

doi:10.1080/10426914.2018.1512114

Cited by 46 publications

(22 citation statements)

References 25 publications

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“…Since residuals are the errors in the fitting, sometimes SSR is also referred to as the sum of squared error in predictions (SSE). ANOVA is then performed to identify and eliminate the non-significant terms of the fitted RSM model [30][31].…”

Section: Response Surface Methodologymentioning

confidence: 99%

Symbolic regression metamodel based multi-response optimization of EDM process

Kumar¹,

Kalita²,

Gao³

2020

FME Transactions

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Electrical Discharge Machining (EDM) is a popular non-traditional machining process that is widely used due to its ability to machine hard and brittle materials. It does not require a cutting tool and can machine complex geometries easily. However, it suffers from drawbacks like a poor rate of machining and excessive tool wear. In this research, an attempt is made to address these issues by using a metamodel coupled with global optimization approach to predict suitable combinations of input parameters (current, pulse on-time and pulse off-time) that would effectively increase the material removal rate and minimize the tool wear. The metamodels are built by using a novel symbolic regression approach carried out using Genetic Programming (GP). On comparative evaluation against traditional response surface methodology (RSM) metamodels, the GP metamodels show much better and accurate estimation. GP metamodels are then coupled with a genetic algorithm to carry out multiobjective optimization of the EDM process.

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Section: Response Surface Methodologymentioning

confidence: 99%

Symbolic regression metamodel based multi-response optimization of EDM process

Kumar¹,

Kalita²,

Gao³

2020

FME Transactions

Self Cite

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“…The model F-value with 3.7404 implies the model is substantial. "Prob > F" higher than 0.05 represents that the model is not significant [27,28]. In such a situation, N, fd, N 2 and f 2 are the most important model terms.…”

Section: Anova Of the Regression Modelmentioning

confidence: 97%

“…In Figure 3, the residuals, internally studentized residuals, and externally studentized residuals are plotted against the predicted response values. It is observed that all the data points show a random scatter, which could mean that the hypothesis that constant variance is maintained is not violated [27]. In Figure 3, the residuals, internally studentized residuals, and externally studentized residuals are plotted against the predicted response values.…”

Section: Analyzing the Regression Modelmentioning

confidence: 99%

Memetic Cuckoo-Search-Based Optimization in Machining Galvanized Iron

et al. 2020

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In this article, an improved variant of the cuckoo search (CS) algorithm named Coevolutionary Host-Parasite (CHP) is used for maximizing the metal removal rate in a turning process. The spindle speed, feed rate and depth of cut are considered as the independent parameters that describe the metal removal rate during the turning operation. A data-driven second-order polynomial regression approach is used for this purpose. The training dataset is designed using an L16 orthogonal array. The CHP algorithm is effective in quickly locating the global optima. Furthermore, CHP is seen to be sufficiently robust in the sense that it is able to identify the optima on independent reruns. The CHP predicted optimal solution presents ±10% deviations in the optimal process parameters, which shows the robustness of the optimal solution.

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“…Diamond is the hardest available material till date. It is very much popular due to its mechanical, thermal and chemical properties [1]. Rapid developmental works were carried out in the last three decades in the research area of CVD diamond coating.…”

Section: Introductionmentioning

confidence: 99%

Study of cutting force and tool wear during turning of aluminium with WC, PCD and HFCVD coated MCD tools

et al. 2020

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Enormous developmental work has been made in synthesis of metastable diamond by hot filament chemical vapor deposition (HFCVD) method. In this paper, micro-crystalline diamond (MCD) was deposited on WC–6 wt.% Co cutting tool inserts by HFCVD technique. The MCD coated tool was characterized by the scanning electron microscope (SEM), X-ray diffraction (XRD) and micro Raman spectroscopy (μ-RS). A comparison was made among the MCD tool, uncoated tungsten carbide (WC) tool and polycrystalline diamond (PCD) tool during the dry turning of rolled aluminum. The various major tests were conducted such as surface roughness, cutting force and tool wear, which were taken into consideration to establish a proper comparison among the advanced cutting tools. Surface roughness was measured during machining by Talysurf. The tool wear was studied by SEM after machining. The cutting forces were measured by Kistler 3D-dynamometer during the machining process. The test results indicate that, the CVD coated MCD tool and PCD tool produced almost similar results. But, the price of PCD tools are five times costlier than MCD tools. So, MCD tool would be a better alternative for machining of aluminium.

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PECVD process parameter optimization: towards increased hardness of diamond-like carbon thin films

Cited by 46 publications

References 25 publications

Symbolic regression metamodel based multi-response optimization of EDM process

Symbolic regression metamodel based multi-response optimization of EDM process

Memetic Cuckoo-Search-Based Optimization in Machining Galvanized Iron

Study of cutting force and tool wear during turning of aluminium with WC, PCD and HFCVD coated MCD tools

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