The Cardinal TOPSIS via Grey Relational Grade

2018 ◽  
Author(s):  
Kunli Wen ◽  
Meili You
Keyword(s):  
Grey Relational Grade ◽  
Grey Relational

scholarly journals Grey Relational Grade Based Quantitative Analysis of the Factors Influencing the Load Characteristics of A Power Grid

2018 ◽  
Vol 53 ◽  
pp. 01012 ◽  
Author(s):  
Wei Pan ◽  
Caijia Lei ◽  
Wei Jia ◽  
Hui Gao ◽  
Binghua Fang
Keyword(s):  
Quantitative Analysis ◽  
Influencing Factors ◽  
Power Grid ◽  
Grey System Theory ◽  
Grey System ◽  
Factors Affecting ◽  
Grey Relational Grade ◽  
Load Characteristics ◽  
Grey Relational ◽  
Main Factor

Regarding analysis of load characteristics of a power grid, there are multiple factors that influence the variation of load characteristics. Among these factors, the influence of different ones on the change of load characteristic is somewhat different, thus the degree of influence of various factors needs to be quantified to distinguish the main and minor factors of load characteristics. Based on this, the grey relational analysis in the grey system theory is employed as the basis of mathematical model in this paper. Firstly, the main factors affecting the load characteristics of a power grid are analysed. Then, the principle of quantitative analysis of the influencing factors by using grey relational grade is introduced. Lastly, the load of Guangzhou power grid is selected as the research object, thereby the main factor of temperature affecting the load characteristics is quantitatively analysed, such that the correlation between temperature and load is established. In this paper, by investigating the influencing factors and the degree of influence of load characteristics, the law of load characteristics changes can be effectively revealed, which is of great significance for power system planning and dispatching operation.

scholarly journals Multi Performance Optimizationof Shoulder Milling Process Parameters of AA6063 T6 Aluminium Alloy by Taguchi Based GRA

2019 ◽  
Vol 8 (10S) ◽  
pp. 420-425
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Analysis Data ◽  
Milling Process ◽  
Depth Of Cut ◽  
Analysis Method ◽  
Relational Analysis ◽  
Grey Relational Grade ◽  
Grey Relational

In this paper, a grey relational analysis method based on Taguchi is proposed to improve the multi-performance characteristics of VMC shoulder milling process parameters in the processing of AA6063 T6. Taking into account four process parameters such as coolant, depth of cut,speed and feed, there are three level of each process parameter in addition to two levels of coolant. 18 experiments were used by L18 orthogonal array using the taguchi method. Multi-performance features like surface roughness and material removal rate are used. Grey Relational Analysis method is used to obtain the Grey Relational Grade, and the multiperformance characteristics of the process are pointed out. Then, the Taguchi response table method and ANOVA are used to analysis data. In order to ensure the validity of the test results, a confirmation test was conducted. The study also shows that this method can effectively improve the multi-function characteristics of shoulder milling process.In his work microstructure and mechanical properties of AA6063 T6before and after shoulder milling have been investigated.

Application of the Grey-Taguchi Method to the Optimization of Metal Injection Molding (MIM) Process

2010 ◽  
Vol 443 ◽  
pp. 63-68 ◽  
Author(s):  
Khairur Rijal Jamaludin ◽  
Norhamidi Muhamad ◽  
Mohd Nizam Ab. Rahman ◽  
Sufizar Ahmad ◽  
Mohd Halim Irwan Ibrahim ◽  
...  
Keyword(s):  
Injection Molding ◽  
Taguchi Method ◽  
Mold Temperature ◽  
Parameter Design ◽  
Metal Injection Molding ◽  
Quality Performance ◽  
Surface Appearance ◽  
Grey Relational Grade ◽  
Grey Relational ◽  
Grey Taguchi

The Grey-Taguchi method was adopted in this study to optimize the injection molding parameters for the MIM green compacts with multiple quality performance. A Grey relational grade obtained from the Grey relational analysis is used as the quality performance in the Taguchi method. Then, the optimum injection molding parameters are determined using the parameter design proposed by the Taguchi method. The result concluded that the mold temperature (D) is very significant, by the fact that the ANOVA shows its contribution to excellent surface appearance as well as strong and dense green compacts is 38.82%.

MCDM-Based Optimization of Performance Characteristics During µEDMing of SS 304

2021 ◽  
pp. 18-32
Author(s):  
Premangshu Mukhopadhyay ◽  
Goutam Kumar Bose ◽  
Pritam Pain
Keyword(s):  
Stainless Steel ◽  
Work Performance ◽  
Research Work ◽  
Performance Characteristics ◽  
Micro Edm ◽  
Grey Relational Grade ◽  
Research Findings ◽  
Micro Features ◽  
Grey Relational ◽  
Edm Process

Micro-EDM is most widely used for developing perfect drilled micro features/parts. Research was carried out to improve the material removal and tool wear of any conductive machined product by EDM and micro-EDM process. In this chapter, RSM was used for designing the experiments with 20 set of experiments. In this present research work, performance characteristics like MRR and Overcut have got a different level of importance. Here the stress was given on MRR rather than on OC. In this MCDM analysis, the weight of MRR is considered to be maximum (i.e., larger is better), and other weights of other responses are considered to be the minimum (i.e., smaller is better). Finally, in the midst of all the combinations of process parameters considered one that acquires the highest grey relational grade is the best parametric combination. The research findings in the area of machining of stainless steel 304 will be helpful to manufacturing engineers for selecting the optimized parametric combinations of micro-EDM process with stainless steel.

Practical state of health estimation of power batteries based on Delphi method and grey relational grade analysis

2015 ◽  
Vol 282 ◽  
pp. 146-157 ◽  
Author(s):  
Bingxiang Sun ◽  
Jiuchun Jiang ◽  
Fangdan Zheng ◽  
Wei Zhao ◽  
Bor Yann Liaw ◽  
...  
Keyword(s):  
Delphi Method ◽  
State Of Health ◽  
Grey Relational Grade ◽  
Grey Relational

Optimizing the Sintering Parameter of Metal Injection Molding Compact Using Robust Engineering Technique

2012 ◽  
Vol 445 ◽  
pp. 357-361
Author(s):  
Khairur Rijal Jamaludin ◽  
Norhamidi Muhamad ◽  
Sufizar Ahmad ◽  
Mohd Halim Irwan Ibrahim ◽  
Nor Hafiez Mohd Nor ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Injection Molding ◽  
Quality Characteristics ◽  
Metal Injection Molding ◽  
Sintered Part ◽  
Multiple Quality Characteristics ◽  
Sintering Time ◽  
Engineering Technique ◽  
Grey Relational Grade ◽  
Grey Relational

Sintering is a key step in the metal injection molding (MIM) process, which affects the mechanical properties of the sintered part. The mechanical properties of the sintered compacts are resulted from tremendous sintered part densification. This work utilizes robust engineering technique in optimizing sintering parameters of metal injection molding compacts. Three quality characteristics; shrinkage, density and flexure strength is optimized using Taguchi method-based grey analysis. The modified algorithm adopted here was successfully used for both detraining the optimum setting of the process parameters and for combining multiple quality characteristics into one integrated numerical value called grey relational grade. The sintering parameters investigated are: sintering temperature, sintering time, and heating rate. The result concluded that sintering time is the most significant for the combination of the quality characteristics.

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