Grey-Fuzzy Modelling and Analysis of Optimizing Turning Process Parameters for Stainless Steel Material

Prasath, V; Kannan, Ramya; Mugesh, R. Shanmuga; Sugeesh, N.; Bharathi, S.; Moshi, A. Arul Marcel

doi:10.1007/978-981-16-4222-7_39

Cited by 2 publications

(3 citation statements)

References 15 publications

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Section: Methodsmentioning

confidence: 99%

“…In the same way, for the case of the output variable, i.e., the grey-fuzzy reasoning grade, nine fuzzy sets have been fixed such as Tiny (T), Very Small (vs.), Small (S), Small Medium (SM), Medium (M), Medium Large (ML), Large (L), Very Large (VL) and Huge (H).The fuzzy rules used for the fuzzy logic controller are given in Table 4. 40,41 The graphical representations of fuzzy logic rules viewer for 'Rank 1' and 'Rank 9' of the experimental combinations are as shown in the Figures 5(a For Rank 1, the input values are given as 0.822 (Grey Relational coefficient of SR) and 1.000 (Grey Relational coefficient of MRR) respectively. The defuzzified output value for Rank 1 combination was obtained as 0.882.…”

Section: Fuzzy Logic Approachmentioning

confidence: 99%

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Machinability Study on CNC Turning of Stainless Steel 303 with CVD Multi-Layer (TiN/Al₂O₃/TiCN) Coated Carbide Insert by using Grey-Fuzzy Logic Approach

Bharathi¹,

Ravindran²,

Moshi³

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part E:

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Manufacturing requires reliable models and methods for the prediction of output performance of machining processes as the demand for highly automated machine tools in the industry has been increased. The prediction of optimal machining conditions for good surface finish and dimensional accuracy plays a very important role in process planning. In the present work, dry turning of austenitic Stainless Steel (SS303) using CVD multi-layer (TiN/Al2O3/TiCN) coated carbide insert has been investigated. Cutting speed, feed rate, and depth of cut have been considered as the input process variables for the dry turning process. Taguchi's L9 orthogonal array has been utilized for designing the experiments. A Grey-Fuzzy logic approach has been employed to investigate the multi-objective optimization of turning process parametric combination to provide minimum Surface Roughness (SR) with the maximum Material Removal Rate (MRR). Analysis of Variance (ANOVA) technique has been employed to identify the most influencing input process variable for achieving minimum SR and maximum MRR. Morphology analysis has been performed on the machined surfaces and the chips generated during the machining processes using a Scanning Electron Microscope (SEM) in order to relate the surface quality with the input factor setting.

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Section: Methodsmentioning

confidence: 99%

Section: Fuzzy Logic Approachmentioning

confidence: 99%

Machinability Study on CNC Turning of Stainless Steel 303 with CVD Multi-Layer (TiN/Al₂O₃/TiCN) Coated Carbide Insert by using Grey-Fuzzy Logic Approach

Bharathi¹,

Ravindran²,

Moshi³

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part E:

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“…Figure 5 shows fuzzy logic model created for the proposed study using MATLAB. The defuzzified crisp value obtained from the analysis is called as 'Grey-fuzzy reasoning grade' (GFRG) [27].…”

Section: Fuzzy Logic Approachmentioning

confidence: 99%

Investigation on the wear rate and COF of AA356 metal matrix composites reinforced with zirconium silicate (ZrSiO₄) particles

Prabhu,

Moshi,

Hariharasakthisudhan

et al. 2023

Surf. Topogr.: Metrol. Prop.

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These days, metal matrix composites (MMCs) are frequently investigated by incorporating the proper reinforcement particles. In order to enhance various properties of the manufactured MMCs, reinforcement particles are embedded into the base metal. In the present investigation, A356 MMCs reinforced with 5 wt.% of zirconium silicate (ZrSiO4) particles have been prepared and tested for the friction and wear behaviour. Utilizing the stir-casting technique, the composites were produced; and the test specimens have been prepared with ASTM G99 standards. Three significant process variables have been considered for performing the wear test such as normal load, sliding velocity and sliding distance. The Taguchi's L9 orthogonal array design has been used to plan the experimental design for the wear test. Main Effect Plots (MEPs) have been drawn for the coefficient of friction (COF) and wear rate values obtained during the test for different combinations of selected input variables, and analyzed. To determine the optimal input variable combinations that lead to lower COF and wear rate, Grey-Fuzzy Reasoning Grade Analysis (GFRGA) has been used. For the taken into account input conditions and the recorded output responses, an artificial neural network (ANN) model has been created. The surfaces of the worn out samples have been tested with the aid of the micrographs taken by a Scanning Electron Microscope (SEM).

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Grey-Fuzzy Modelling and Analysis of Optimizing Turning Process Parameters for Stainless Steel Material

Cited by 2 publications

References 15 publications

Machinability Study on CNC Turning of Stainless Steel 303 with CVD Multi-Layer (TiN/Al₂O₃/TiCN) Coated Carbide Insert by using Grey-Fuzzy Logic Approach

Machinability Study on CNC Turning of Stainless Steel 303 with CVD Multi-Layer (TiN/Al₂O₃/TiCN) Coated Carbide Insert by using Grey-Fuzzy Logic Approach

Investigation on the wear rate and COF of AA356 metal matrix composites reinforced with zirconium silicate (ZrSiO₄) particles

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Grey-Fuzzy Modelling and Analysis of Optimizing Turning Process Parameters for Stainless Steel Material

Cited by 2 publications

References 15 publications

Machinability Study on CNC Turning of Stainless Steel 303 with CVD Multi-Layer (TiN/Al2O3/TiCN) Coated Carbide Insert by using Grey-Fuzzy Logic Approach

Machinability Study on CNC Turning of Stainless Steel 303 with CVD Multi-Layer (TiN/Al2O3/TiCN) Coated Carbide Insert by using Grey-Fuzzy Logic Approach

Investigation on the wear rate and COF of AA356 metal matrix composites reinforced with zirconium silicate (ZrSiO4) particles

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Product

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Machinability Study on CNC Turning of Stainless Steel 303 with CVD Multi-Layer (TiN/Al₂O₃/TiCN) Coated Carbide Insert by using Grey-Fuzzy Logic Approach

Machinability Study on CNC Turning of Stainless Steel 303 with CVD Multi-Layer (TiN/Al₂O₃/TiCN) Coated Carbide Insert by using Grey-Fuzzy Logic Approach

Investigation on the wear rate and COF of AA356 metal matrix composites reinforced with zirconium silicate (ZrSiO₄) particles