Optimization of grinding titanium with 2%CNT-CBN wheel using TOPSIS

Stephen, Deborah Serenade; Sethuramalingam, Prabhu

doi:10.1080/10426914.2022.2039696

Cited by 12 publications

(4 citation statements)

References 27 publications

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“…Consequently, a comparative study of the acquired findings from the three MCDM approaches employed in this work is one of the primary goals envisioned as a result of this effort. Table (7) From Table (7) and Figure (1), the following observations are proposed: 1. The ranking order of choices differs across the three approaches.…”

Section: Comparison Of Results Obtained Using Mcdm Methodsmentioning

confidence: 99%

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Optimization of Submerged Arc Welding Setting Parameters Using Taguchi-Based MCDM Techniques : A Comparative Analysis

Eisa

2022

ERJ. Engineering Research Journal

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The process parameters' right choice is a major problem for researchers. The sectors' decision-makers must consider a large diversity of attributes based on a group of contradicting criteria. Multi-criteria decision-making (MCDM) techniques are applied to enhance the selection of these parameters. This paper examines using the VIKOR, MOORA, and TOPSIS methodologies to determine the optimal arrangement of processing factors in submerged arc welding (SAW). Consideration is given to one case study on optimization. This case study depends on the experimental work conducted on the SAW of Cr-Mo-V steel. Significant parameters of the input process are wire feed, welding current, voltage, and speed. The influence of these factors on different responses about weld penetration, bead width, tensile strength, weld reinforcement, and weld hardness is investigated. Comparing the TOPSIS, VIKOR, and MOORA procedures demonstrate that all three techniques have shown similar results and are interchangeable. The Taguchi analysis-based TOPSIS technique is compared to the QO-Jaya algorithm, Jaya algorithm, and (TLBO) teaching learning-based optimization.

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Section: Comparison Of Results Obtained Using Mcdm Methodsmentioning

confidence: 99%

“…A quick overview of several noteworthy research papers has been presented in this regard. Numerous machining procedures have utilized the TOPSIS technique., such as grinding by Stephen et al [7], electrical discharge machining by Huu-Quang Nguyen et al [8], and Zeng. et al [9].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Submerged Arc Welding Setting Parameters Using Taguchi-Based MCDM Techniques : A Comparative Analysis

Eisa

2022

ERJ. Engineering Research Journal

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“…The TOPSIS method is one of the two objective optimization methods where the positive hypothesis and worst solution negative hypothesis are also considered [17].…”

Section: Topsis Methods For Cuboid Fdm Modelmentioning

confidence: 99%

Experimental Study and Predictive Modelling of Fused Deposition Modelling (FDM) Using TOPSIS and Fuzzy Logic Expert System

Sethuramalingam

Jaishwin

et al. 2023

Int. J. Automot. Mech. Eng.

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Fused deposition modeling (FDM) is a well-liked additive fabrication method used to manufacture prototypes and components in industries. The quality of the 3D printed component depends on the temperature profile between the layers of the printed components and the process parameters. The deviations in the quality of manufactured components can be established using tools of metrology, including Coordinate-Measuring Machine and Machine Vision. This research is to determine the effect of temperature on the aforementioned phenomenon by using collected data to build a predictive model. The leading factor effect intrigue is stressed for the correlative closeness coefficient (Cn*) and Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS). The most favorable combinations of the experiment were obtained from the response diagram at a layer thickness of 0.3 mm, print speed of 80 mm/sec, and infill percentage of 20%. It is noted that the parameters have a contribution of 55.60%, 33.16%, and 0.15%, respectively. The majority of agreeable combinations of the investigations were acquired from the main factor effect response diagram, a layer thickness of 0.3 mm, printing FDM speed of 80 mm/sec, and an infill percentage of material is 20% for maximizing the temperature gradient and minimizing shrinkage and warpage. A fuzzy logic expert system was used to predict the shrinkage allowances precisely with less than 5% error.

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“…G. Xiao and S. Malkin [25] conducted online-optimizing, the internal grinding process, and the dressing parameters to reduce the production time while maintaining part quality requirements. The optimum process parameters when grinding Ti-6Al-4 V using a CBN grinding wheel was introduced in [26]. The Taguchi method and gray relational analysis (GRA) were applied to find the optimum dressing parameters when processing the SKD11 tool steel in surface grinding to increase the material removal rate and to reduce the roundness tolerance of the ground parts [11].…”

Section: Introductionmentioning

confidence: 99%

Determining the Best Dressing Parameters for External Cylindrical Grinding Using MABAC Method

Hoang

Trieu

et al. 2022

Applied Sciences

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Multi-criteria decision making (MCDM) is a research area that entails analyzing various available options in a situation involving social sciences, medicine, engineering, and many other fields. This is due to the fact that it is used to select the best solution from a set of alternatives. The MCDM methods have been applied not only in economics, medicine, transportation, and the military, but also in mechanical processing processes to determine the best machining option. In this study, determining the best dressing mode for external grinding SKD11 tool steel using an MCDM method—the MABAC (multi-attributive border approximation area comparison) method—was introduced. The goal of this research is to find the best dressing mode for achieving the minimal surface roughness (RS), the maximum wheel life (T), and the minimal roundness (R) all at the same time. To perform this work, an experiment was carried out with six input parameters: the fine dressing depth, the fine dressing passes, the coarse dressing depth, the coarse dressing passes, the non-feeding dressing, and the dressing feed rate. In addition, the Taguchi method and an L16 orthogonal array were used to design the experiment. Furthermore, the MEREC (method based on the removal effects of criteria) and entropy methods were used to determine the weight of the criteria. The best dressing mode for external cylindrical grinding has been proposed based on the results. These findings were also confirmed by comparing them to the TOPSIS (technique for order of preference by similarity to ideal solution) and MARCOS (measurement of alternatives and ranking according to compromise solution) methods.

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Optimization of grinding titanium with 2%CNT-CBN wheel using TOPSIS

Cited by 12 publications

References 27 publications

Optimization of Submerged Arc Welding Setting Parameters Using Taguchi-Based MCDM Techniques : A Comparative Analysis

Optimization of Submerged Arc Welding Setting Parameters Using Taguchi-Based MCDM Techniques : A Comparative Analysis

Experimental Study and Predictive Modelling of Fused Deposition Modelling (FDM) Using TOPSIS and Fuzzy Logic Expert System

Determining the Best Dressing Parameters for External Cylindrical Grinding Using MABAC Method

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