Use of the grey relational analysis method to determine the important environmental factors that affect the atmospheric corrosion of Q235 carbon steel

2015 ◽  
Vol 62 (1) ◽  
pp. 7-12 ◽  
Author(s):  
Xianlong Cao ◽  
Hongda Deng ◽  
Wei Lan
Keyword(s):  
Carbon Steel ◽  
Environmental Factors ◽  
Grey Relational Analysis ◽  
Atmospheric Corrosion ◽  
Analysis Method ◽  
Grey System ◽  
Content Type ◽  
Relational Analysis ◽  
Q235 Carbon Steel ◽  
Grey Relational

Purpose – The purpose of this study was to evaluate the grey relational analysis method as a way of determining quickly the important factors affecting the atmospheric corrosion of Q235 carbon steel in one year. Design/methodology/approach – Atmospheric corrosion exposure tests on Q235 steel were carried out at seven typical test sites in China. The test period lasted one year. The corrosion rate of the Q235 test panels was determined using the weight-loss method and environmental factors were monitored and recorded by standard methods. The importance of the various environmental factors was evaluated using the grey relational analysis method. Findings – The results obtained by the grey relational analysis method showed that the ranking order of factors affecting the corrosion of Q235 carbon steel from “slightly” to “severely” was as follows: relative humidity > dew days > SO3 > pH value of rain > rain precipitation > temperature > rainy days > Cl− > H2S > NO2. Furthermore, the initial atmospheric corrosion of Q235 carbon steel was recognized as being the corrosion of the smooth surface by water medium, or acidic aqueous solution. Originality/value – Materials corrosion can be defined as a grey system because corrosion has a clear outcome and complex but uncertain characteristics. The grey relational analysis method, a part of grey system theory, is an effective and quick data processing method that can be used to sort out the degree of correlation of environmental factors affecting atmospheric corrosion in terms of it being a grey system with a lot uncertain information.

The proof of a new modified grey relational grade

2016 ◽  
Vol 6 (2) ◽  
pp. 180-186 ◽  
Author(s):  
Kunli Wen
Keyword(s):  
System Theory ◽  
Grey Relational Analysis ◽  
Design Methodology ◽  
Grey System Theory ◽  
Grey System ◽  
Content Type ◽  
The Past ◽  
Relational Analysis ◽  
Grey Relational Grade ◽  
Grey Relational

Purpose – Until now, many different varieties of grey relational grade methods had been proposed, and there are also many relevant publications. However, in one article published in 2007, which applied the previous grey relational grade to environmental protection fields and some results had been found. After studied it carefully, the author found that the grey relational grade in the paper was not the previous grey relational grade. According to the mathematics logic, it must first prove the proposed grey relational grade satisfies the four axioms in grey relational analysis, and then the author can say that the achieved results are reasonable and correct. The paper aims to discuss these issues. Design/methodology/approach – The paper lists the rational and regular grey relational grade that had been published in the past, and used the four axioms in grey system theory to prove the Pai’s grey relational grade that satisfy the four axioms steps by steps. Findings – Through the detail proof of the proposed grey relational grade in Pai’s paper, it indeed satisfies the four axioms in grey relational grade. Research limitations/implications – The paper had enhanced the correctness and reasonableness of that paper, and let the grey relational grade, which appear in Pai’s paper is legitimate and correct grey relational grade in grey system theory. Originality/value – The paper had identified that Pai’s grey relational grade is a rational and regular grey relational grade in grey system theory, and it proves that the results in Pai’s paper are correct and reasonable.

The most livable city selection in Turkey with the grey relational analysis

2020 ◽  
Vol 10 (4) ◽  
pp. 529-544 ◽  
Author(s):  
Erkan Kose ◽  
Danışment Vural ◽  
Gulcin Canbulut
Keyword(s):  
System Theory ◽  
Grey Relational Analysis ◽  
Complex Problem ◽  
Grey System Theory ◽  
Grey System ◽  
Content Type ◽  
Relational Analysis ◽  
Decision Points ◽  
Criteria Weights ◽  
Grey Relational

PurposeThis study has two main objectives: (1) to expand the application areas of grey system theory and (2) to select the most livable city in Turkey.Design/methodology/approachChoosing the most livable city is a complex problem that requires many criteria to be considered. It is important to select decision points according to which the criteria selection will be made and to what extent the criteria will affect the evaluation. For this purpose, a questionnaire was prepared to determine the criteria to be used in the assessment. The survey results were evaluated by the factor analysis (FA) and it was found that the criteria included in the survey were grouped under seven factors. Then, criteria weights were assigned to the determined criteria using the analytic hierarchy process (AHP). At the last stage, Turkey's six most popular cities are graded using the grey relational analysis (GRA) to reduce the uncertainty existing in the process of evaluation.FindingsThe obtained results indicated that the most livable city in Turkey is Istanbul. Istanbul is followed by Izmir, Antalya, Eskisehir, Bursa and Ankara, respectively. Considering that Istanbul is a center of attraction in many respects, this result is not a surprise for many people. It is also observed that the results obtained overlap with similar studies in the literature.Originality/valueGrey system theory and grey numbers have not been previously used to select the most livable city. With this aspect, this study has expanded the application of grey system theory and made an important contribution to the literature.

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.

Quality improvement of smart senior care service platform in China based on grey relational analysis and Fuzzy-QFD

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lan Xu ◽  
Yu Zhang
Keyword(s):  
Quality Improvement ◽  
Grey Relational Analysis ◽  
Care Service ◽  
The Elderly ◽  
Service Platform ◽  
Content Type ◽  
Relational Analysis ◽  
Improvement Method ◽  
Grey Relational ◽  
Quality Improvement Method

PurposeSmart senior care industry in China currently faces a series of practical difficulties such as an imbalance in the demand and supply structure, service products unable to cater to the actual needs of the elderly and a low degree of marketization. This study therefore proposes using grey relational analysis and the Fuzzy-quality function development (QFD) quality improvement method to help solve these problems.Design/methodology/approachThe proposed method converts the fuzzy requirements of the elderly into the technical characteristics of technologically augmented senior care service products. It then, uses the QFD relationship matrix, combined with grey relational analysis, to analyze the relationship between the needs of elderly and the converted technical characteristics, and subsequently identifies key technical characteristics.FindingsResults show that an improvement in the smart senior care service platform according to the differences of the elderly's preferences can significantly improve users' satisfaction with the service in addition to enhancing market competitiveness of the technologically assisted senior care service products.Originality/valueA novel method to improve the need of smart senior care is proposed by considering age difference. The proposed grey relational analysis and Fuzzy-QFD quality improvement method can help improve the service quality of the smart senior care service platform.

Negative grey relational model and measurement of the reverse incentive effect of fields medal

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sifeng Liu
Keyword(s):  
Grey Relational Analysis ◽  
Research Output ◽  
Analysis Model ◽  
Content Type ◽  
Relational Analysis ◽  
Fields Medal ◽  
Definition Of ◽  
Grey Relational ◽  
Analysis Models ◽  
The Relationship

PurposeThe purpose of this paper is to construct some negative grey relational analysis models to measure the relationship between reverse sequences.Design/methodology/approachThe definition of reverse sequence has been given at first based on analysis of relative position and change trend of sequences. Then, several different negative grey relational analysis models, such as the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model have been put forward based on the corresponding common grey relational analysis models. The properties of the new models have been studied.FindingsThe negative grey relational analysis models proposed in this paper can solve the problem of relationship measurement of reverse sequences effectively. All the new negative grey relational degree satisfying the requirements of normalization and reversibility.Practical implicationsThe proposed negative grey relational analysis models can be used to measure the relationship between reverse sequences. As a living example, the reverse incentive effect of winning Fields Medal on the research output of winners is measured based on the research output data of the medalists and the contenders using the proposed negative grey relational analysis model.Originality/valueThe definition of reverse sequence and the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model are first proposed in this paper.

Selection of Molybdenum-Filled Hip Implant Material Using Grey Relational Analysis Method

2018 ◽  
pp. 675-692 ◽  
Author(s):  
Amit Aherwar ◽  
Amit Singh ◽  
Amar Patnaik ◽  
Deepak Unune
Keyword(s):  
Grey Relational Analysis ◽  
Testing Machine ◽  
Base Material ◽  
Analysis Method ◽  
Wear Properties ◽  
Hardness Tester ◽  
Relational Analysis ◽  
Implant Material ◽  
Pin On Disc ◽  
Grey Relational

In this study, a series of implant material containing molybdenum of different weight percentages were fabricated via high temperature vertical vacuum casting induction furnace and examined their physical, mechanical and wear properties. The mechanical properties were tested by the micro-hardness tester and the compression testing machine, while the wear performance was analyzed through a pin-on-disc tribometer under different operating conditions at room temperature. Density, hardness, compressive strength and sliding wear were considered as criterions for this study. The proportions of alternatives consist of Co-30Cr as a base material and molybdenum as an alloying element which was varied from 0 to 4wt.%. Due to the conflict between the properties obtained, the Grey relational analysis method (GRA) was applied to choose the best material among the set of alternatives. From the results obtained, it was found that Co-30Cr implant material containing 4wt.%molybdenum provides the best combination of the properties for a given application (i.e. hip femoral head).

Disturbing Load Classification Based on the Grey Relational Analysis Method and Load Performance Index

2019 ◽  
Vol 31 (1) ◽  
pp. 141-152
Author(s):  
Alexandre C. Moreira ◽  
Wesley A. de Souza ◽  
Bruna R. P. Conrado ◽  
Helmo K. Morales-Paredes
Keyword(s):  
Grey Relational Analysis ◽  
Performance Index ◽  
Analysis Method ◽  
Relational Analysis ◽  
Grey Relational

Appliance on Evaluation of Type Selection for Agricultural Machinery Based on Grey Relational Analysis Method

2011 ◽  
Vol 55-57 ◽  
pp. 988-991 ◽  
Author(s):  
Yan Xie ◽  
Mu Li
Keyword(s):  
Grey Relational Analysis ◽  
Analysis Method ◽  
Agricultural Machinery ◽  
Analysis Model ◽  
Relational Analysis ◽  
Type Selection ◽  
The Index System ◽  
Selection For ◽  
Grey Relational ◽  
Optimal Type

The type selection for agricultural machinery generally depends on the selector’s experiences at the present time. It exist some subjectivity and one-sidedness unavoidably. On the basis of the characteristics of complexity and the uncertainty of optimal selection for agricultural machinery, grey relational analysis model in agricultural machinery multi-type selection application has been put forward in this paper. The index system of influencing agricultural machinery type selection is determined. Application model and procedures of the grey relational analysis method are introduced. According to the degree how close it is with the ideal dot, the optimal type is easy to be selected out. Through the optimization analysis type selection for the agricultural transporter, it is proved that the optimal type selection for agricultural machinery based on grey relational analysis has the strong recognition judgment ability. It is convenient, quantitative, and strict. It provided a new method and a possible new way for evaluation of agricultural machinery type selecting．

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