Multi-Criteria Decision Making in the Powder-Mixed Electrical Discharge Machining Process Based on the Cocoso, Spotis Algorithms and the Weighting Methods

Bui, Huy-Anh; Tran, Ngoc-Tien; Nguyen, D. T.

doi:10.54684/ijmmt.2023.15.1.69

Cited by 3 publications

(1 citation statement)

References 25 publications

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“…In [16], the authors extended the SPOTIS method to fuzzy environments to avoid rank reversal in multi-criteria problems, and the results showed its effectiveness in objectively evaluating criteria. The combination of SPOTIS with other methods has also proven to be effective, as seen in its application in decision-making for the powder-mixed electrical discharge machining process [17]. COMET is another widely used MCDM method that allows for the identification of the entire domain model, providing objectives and reliable recommendations based on gathered data [18].…”

Section: Introductionmentioning

confidence: 99%

Application of the multi-criteria analysis method mairca, spotis, comet for the optimisation of sustainable electricity technology development

Tran

2024

Eureka: PE

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The development of sustainable electricity technology is of utmost importance in addressing the increasing energy demand while mitigating greenhouse gas emissions. Fossil fuel-based electricity generation is the primary contributor to air pollution and climate change, necessitating a shift towards renewable energy sources. The efficient production, distribution, and utilization of energy resources, along with ensuring affordable energy access and environmental sustainability, are key policy objectives for any country's energy sector. However, assessing sustainable electricity technologies is a complex task due to the diverse range of evaluation criteria and impacts associated with the practical implementation of these solutions. To overcome this challenge, this study proposes a multi-criteria decision-making (MCDM) approach to select the optimal solution for the development of sustainable electricity technology. The study employs several reliable methods, including MAIRCA, SPOTIS, COMET, and the CRITIC weighting method, to perform ranking evaluations. Based on this, an evaluation Table of criteria using linguistic variables is constructed. Furthermore, a ranking of methods for developing sustainable electricity technology is established by combining MCDM optimization methods. The results indicate that future energy policies should prioritize sustainable energy technologies, particularly water and solar thermal solutions. These findings have significant implications for development policymakers as the transition towards a sustainable energy system becomes increasingly crucial. In the future, the findings of this research can be further developed on a regional level, enabling the identification of the most appropriate energy technologies for specific regions based on their unique characteristics and requirements

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Section: Introductionmentioning

confidence: 99%

Application of the multi-criteria analysis method mairca, spotis, comet for the optimisation of sustainable electricity technology development

Tran

2024

Eureka: PE

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Evaluation of CNC lathe machine with fuzzy linguistic mcdm methods

Nhu,

Phan,

Tran

2024

Eureka: PE

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CNC (Computerized Numerical Control) lathes have become integral to modern manufacturing and machining industries due to their ability to produce intricate parts with precision and efficiency. Not only do CNC lathes enhance productivity and accuracy, but they also minimize human error and enhance overall safety in the manufacturing process. Furthermore, the current market offers a wide array of diverse types of CNC lathes. Consequently, the evaluation and selection of CNC lathes pose a complex decision-making challenge as there are numerous types available, each with a variety of selection criteria for manufacturers to consider. It is crucial to make an informed choice, as improper evaluation and selection can have adverse effects on the overall performance of the production system. In this study, we propose using the fuzzy EDAS (Evaluation Based on Distance from Average Solution) model to evaluate and select CNC lathes. Initially, we employ the fuzzy analysis method, based on expert opinions, to establish a set of weights for the evaluation criteria. These criteria consist of seven factors: capital cost, spindle speed, distance between centers, rapid traverse rates in the X-axis and Z-axis, maximum machining diameter, and maximum machining length. Subsequently, the fuzzy EDAS object ranking model is utilized to evaluate and rank the CNC lathes, ultimately aiding in the selection of the most suitable machine for the manufacturer. The results obtained from our analysis reveal that the MICROTURN-300DX machine is the optimal choice, closely followed by the MICROTURN-300X machine. The study's findings serve as valuable guidelines for decision makers in selecting CNC lathes that align with the requirements of factory production. Moreover, the suggested approach can also be utilized to choose various other machine types as production demands become more intricate

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Multi-Objective Optimization of Machining Parameters for Edm of Magnesium Alloy- Ze41 Using Marcos Algorithm and Different Weighing Methods: Sd, Critic and Merec

Uyala,

Jannu

et al. 2024

IJMMT

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This paper presents multi-objective optimization of machining parameters, i.e., electrode materials, peak current, pulse on time and pulse off time in EDM of magnesium alloy-ZE41. The objectives such as metal removal rate, tool wear rate, surface roughness, recast layer thickness and radial overcut were optimized using MARCOS algorithm and three objective weighing methods, i.e., SD, CRITIC and MEREC. Taguchi’s L27(34) orthogonal array was used for conduction of experiments. ANOVA results showed that electrode material, interaction of electrode material and peak current and pulse on time were the most significant parameters for all weighing methods. Comparative study indicated that the percentage improvement in performance at optimal parameter setting were 37.21%, 32.30% and 10.68% for SD, CRITIC and MEREC respectively. Confirmation results indicated that all objectives except tool wear rate were improved positively for SD and CRITIC, but all objectives except metal removal rate deteriorated for MEREC.

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Multi-Criteria Decision Making in the Powder-Mixed Electrical Discharge Machining Process Based on the Cocoso, Spotis Algorithms and the Weighting Methods

Cited by 3 publications

References 25 publications

Application of the multi-criteria analysis method mairca, spotis, comet for the optimisation of sustainable electricity technology development

Application of the multi-criteria analysis method mairca, spotis, comet for the optimisation of sustainable electricity technology development

Evaluation of CNC lathe machine with fuzzy linguistic mcdm methods

Multi-Objective Optimization of Machining Parameters for Edm of Magnesium Alloy- Ze41 Using Marcos Algorithm and Different Weighing Methods: Sd, Critic and Merec

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