Case Retrieval Strategy of Turning Process Based on Grey Relational Analysis

To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform,a case-based reasoning framework is proposed.Specifically,a Hamming distance and Euclidean distance combined method is designed to measure the similarity of case features which have both numeric and category properties.In addition,AHP(Analytic Hierarchy Process)and entropy weight method are integrated to provide features weight,where both user preferences and comprehensive impact of the index have been concerned.Grey relation analysis is used to obtain the similarity of a new problem and alternative cases.Finally,a platform is also developed on Visual Studio 2015,and a case study is demonstrated to verify the practicality and efficiency of the proposed method.This method can obtain cutting parameters which is suitable without iterative calculation.Compared with the traditional PSO(Particle swarm optimization algorithm)and GA(Genetic algorithm),it can obtain faster response speed.This method can provide ideas for selecting processing parameters in industrial production.While guaranteeing the characteristic information is similar,this approach can select processing parameters which is the most appropriate for the production process and a lot of time can be saved.

Materials Selection of Thermoplastic Matrices of Natural Fibre Composites for Cyclist Helmet Using an Integration of DMAIC Approach in Six Sigma Method Together with Grey Relational Analysis Approach

Natural fibre reinforced polymer composite(NFRPC)materials are gaining popularity in the modern world due to their eco-friendliness,lightweight nature,life-cycle superiority,biodegradability,low cost,and noble mechanical properties.Due to the wide variety of materials available that have comparable attributes and satisfy the requirements of the product design specification,material selection has become a crucial component of design for engineers.This paper discusses the study’s findings in choosing the suitable thermoplastic matrices of Natural Fibre Composites for Cyclist Helmet utilising the DMAIC,and GRA approaches.The results are based on integrating two decision methods implemented utilising two distinct decision-making approaches:qualitative and quantitative.This study suggested thermoplastic polyethylene as a particularly ideal matrix in composite cyclist helmets during the selection process for the best thermoplastic matrices material using the 6σtechnique,with the decision based on the highest performance,the lightest weight,and the most environmentally friendly criteria.The DMAIC and GRA approach significantly influenced the material selection process by offering different tools for each phase.In the future study,selection technique may have been more exhaustive if more information from other factors had been added.

Multi-Criteria Group Decision-Making Method Based on an Improved Single-Valued Neutrosophic Hamacher Weighted Average Operator and Grey Relational Analysis

This paper proposes a multi-criteria decision-making (MCGDM) method based on the improved single-valued neutrosophic Hamacher weighted averaging (ISNHWA) operator and grey relational analysis (GRA) to overcome the limitations of present methods based on aggregation operators. First, the limitations of several existing single-valued neutrosophic weighted averaging aggregation operators (i.e. , the single-valued neutrosophic weighted averaging, single-valued neutrosophic weighted algebraic averaging, single-valued neutrosophic weighted Einstein averaging, single-valued neutrosophic Frank weighted averaging, and single-valued neutrosophic Hamacher weighted averaging operators), which can produce some indeterminate terms in the aggregation process, are discussed. Second, an ISNHWA operator was developed to overcome the limitations of existing operators. Third, the properties of the proposed operator, including idempotency, boundedness, monotonicity, and commutativity, were analyzed. Application examples confirmed that the ISNHWA operator and the proposed MCGDM method are rational and effective. The proposed improved ISNHWA operator and MCGDM method can overcome the indeterminate results in some special cases in existing single-valued neutrosophic weighted averaging aggregation operators and MCGDM methods.

Grey Relational Analysis between Chlorophyll a and Environmental Factors in ShaHu Lake

[Objective] The aim was to explore effects of environmental factors on the content of Chlorophyll a in ShaHu Lake.[Method] Based on the data in Shahu Lake from November in 2007 to September in 2008,the relationship between chlorophyll a and environmental factors like water temperature,pH,secchi-depth （SD）,total nitrogen,total phosphorus and potassium permanganate index was studied by grey relational analysis method.[Result] The main environmental factors affecting the content of Chlorophyll a in ShaHu Lake were in order of water temperature potassium permanganate index 〉total nitrogen 〉pH〉 total phosphorus 〉SD.[Conclusion] The research provides reference for the control of eutrophication and the reasonable development and utilization of Shahu Lake.

Insulation fault diagnosis based on group grey relational grade analysis method for power transformers

Utilising dissolved gases analysis, a new insulation fault diagnosis methodfor power transformers is proposed. This method is based on the group grey relational grade analysismethod. First, according to the fault type and grey reference sequence structure, some typicalfault samples are divided into several sets of grey reference sequences. These sets are structuredas one grey reference sequence group. Secondly, according to a new calculation method of the greyrelational coefficient, the individual relational coefficient and grade are computed. Then accordingto the given calculation method for the group grey relation grade, the group grey relational gradeis computed and the group grey relational grade matrix is structured. Finally, according to therelational sequence, the insulation fault is identified for power transformers. The results of alarge quantity of instant analyses show that the proposed method has higher diagnosis accuracy andreliability than the three-ratio method and the traditional grey relational method. It has goodclassified diagnosis ability and reliability.

Study on effectiveness evaluation of weapon systems based on grey relational analysis and TOPSIS

To evaluate the effectiveness of weapon systems, the advantages and disadvantages of grey relational analysis and TOPSIS for multiattribute decision-making is pointed out, and an effectiveness evaluation model of weapon systems by combining grey relational analysis and TOPSIS is proposed. The model aggregates the grey relational grade and the distance to a new integrated closeness and reflects not only the trend but also the situation of the alternative. The example illuminates that the model is effective for the effectiveness evaluation of weapon systems.

Research on evaluations of several grey relational models adapt to grey relational axioms

Grey relational analysis is an important part of the grey systems theory, and it is the basis of the grey clustering analysis, grey decision-making and grey controlling. To research whether grey relational models satisfy the four grey relational theorems, several kinds of grey relational models are commented. Some problems including the properties of normality, pair symmetry and wholeness are discussed. The phenomenon that the lower value of almost each grey relational model is not equal to zero is proved. The contradiction problems between the properties of wholeness and pair symmetry are verified. Finally, several propositions are constructed to explain the above problems.

Grey relational analysis on the relation between marine environmental factors and oxidation-reduction potential

The effects of marine environmental factors-temperature （T）, dissolved oxygen （DO）, salinity （S） and pH--on the oxidation-reduction potential （ORP） of natural seawater were studied in laboratory. The results show an indistinct relationship between these four factors and the ORE but they did impact the ORP. Common mathematical methods were not applicable for describing the relationship. Therefore, a grey relational analysis （GRA） method was developed. The degrees of correlation were calculated according to GILA and the values of T, pH, DO and S were 0.744, 0.710, 0.692 and 0.690, respectively. From these values, the relations of these factors to the ORP could be described and evaluated, and those of T and pH were relatively major. In general, ORP is influenced by the synergic effect of T, DO, pH and S, with no single factor having an outstanding role.

Function chain neural network prediction on heat transfer performance of oscillating heat pipe based on grey relational analysis

As for the factors affecting the heat transfer performance of complex and nonlinear oscillating heat pipe (OHP),grey relational analysis (GRA) was used to deal with the relationship between heat transfer rate of a looped copper-water OHP and charging ratio,inner diameter,inclination angel,heat input,number of turns,and the main influencing factors were defined.Then,forecasting model was obtained by using main influencing factors (such as charging ratio,interior diameter,and inclination angel) as the inputs of function chain neural network.The results show that the relative average error between the predicted and actual value is 4%,which illustrates that the function chain neural network can be applied to predict the performance of OHP accurately.

Response surface method using grey relational analysis for decision making in weapon system selection

A proper weapon system is very important for a na- tional defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multiple- attribute decision making （MADM） problem. This paper proposes a new mathematical model based on the response surface method （RSM） and the grey relational analysis （GRA）. RSM is used to obtain the experimental points and analyze the factors that have a significant impact on the selection results. GRA is used to an- alyze the trend relationship between alternatives and reference series. And then an RSM model is obtained, which can be used to calculate all alternatives and obtain ranking results. A real world application is introduced to illustrate the utilization of the model for the weapon selection problem. The results show that this model can be used to help decision-makers to make a quick comparison of alternatives and select a proper weapon system from multiple alternatives, which is an effective and adaptable method for solving the weapon system selection problem.

Comprehensive security risk factor identification for small reservoirs with heterogeneous data based on grey relational analysis model

Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when data are incomplete.The existing grey relational models have some disadvantages in measuring the correlation between categorical data sequences.To this end,this paper introduces a new grey relational model to analyze heterogeneous data.In this study,a set of security risk factors for small reservoirs was first constructed based on theoretical analysis,and heterogeneous data of these factors were recorded as sequences.The sequences were regarded as random variables,and the information entropy and conditional entropy between sequences were measured to analyze the relational degree between risk factors.Then,a new grey relational analysis model for heterogeneous data was constructed,and a comprehensive security risk factor identification method was developed.A case study of small reservoirs in Guangxi Zhuang Autonomous Region in China shows that the model constructed in this study is applicable to security risk factor identification for small reservoirs with heterogeneous and sparse data.

Multi-response optimization of process parameters in friction stir welded AM20 magnesium alloy by Taguchi grey relational analysis

The purpose of this paper is to optimize the process parameter to get the better mechanical properties of friction stir welded AM20 magnesium alloy using Taguchi Grey relational analysis(GRA).The considered process parameters are welding speed,tool rotation speed,shoulder diameter and plunging depth.The experiments were carried out by using Taguchi's L18 factorial design of experiment.The processes parameters were optimized and ranked the parameters based on the GRA.The percentage influence of each process parameter on the weld quality was also quantified.A validation experimental run was conducted using optimal process condition,which was obtained from the analysis,to show the improvement in mechanical properties of the joint.This study also shows the feasibility of the GRA with Taguchi technique for improvement in welding quality of magnesium alloy.

Application of grey relational analysis in sheet metal forming for multi-response quality characteristics

The theory of grey systems is a new technique for performing prediction, relational analysis and decision making in many areas. In this paper, the use of grey relational analysis for optimizing the square hole flanging process parameters with considerations of the multiple response (the average flanging height, regular flanging and maximum strain) is introduced. Various flanging parameters, such as the blank inner radius rb, blank inner width B0, are considered. An orthogonal array is used for the experimental design. Multiple response values are obtained using finite element analysis (FEA). Optimal process parameters are determined by the grey relational grade obtained from the grey relational analysis for multi-performance characteristics (flanging height, regular flanging and maximum strain). Analysis of variance (ANOVA) for the grey relational grade is implemented. The results showed good agreement with the experiment result. Grey relational analysis can be applied in multiple response optimi-zation designs.

Optimization of green sand mould system using Taguchi based grey relational analysis

The strength of the mould cavity in sand casting is very much significant to attain high-quality castings. Optimization of green sand process parameters plays a vital role in minimizing casting defects. In the present research work, the effect of process parameters such as AFS grain fineness number, water, molasses, bentonite, fly ash, and ramming, and their levels on the resultant mould properties were investigated and optimized using Taguchi based grey relational analysis. The Taguchi L18 orthogonal array and analysis of variance(ANOVA) were used. The quality characteristics viz., green compression strength, permeability, bulk density, mould hardness and shatter index of green sand mould were optimized using grey relational grade, based on the experiments designed using Taguchi's Design of Experiments. ANOVA analysis indicated that water content is the most influential parameter followed by bentonite, and degree of ramming that contributes to the quality characteristics. The results are confirmed by calculating confidence intervals, which lies within the interval limits. Finally, microstructure observations and X-ray diffraction analysis have been performed for the optimal sand parametric combination. Results show that presence of maximum amount of SiO_2, which might be the reason for enhancement of the physical properties of the sand.

Optimization of cutting parameters with Taguchi and grey relational analysis methods in MQL-assisted face milling of AISI O2 steel

This study aims to examine the usability of environmentally harmless vegetable oil in the minimum quantity of lubrication(MQL)system in face milling of AISI O2 steel and to optimize the cutting parameters by different statistical methods.Vegetable oil was preferred as cutting fluid,and Taguchi method was used in the preparation of the test pattern.After testing with the prepared test pattern,cutting performance in all parameters has been improved according to dry conditions thanks to the MQL system.The highest tool life was obtained by using cutting parameters of 7.5 m cutting length,100 m/min cutting speed,100 mL/h MQL flow rate and 0.1 mm/tooth feed rate.Optimum cutting parameters were determined according to the Taguchi analysis,and the obtained parameters were confirmed with the verification tests.In addition,the optimum test parameter was determined by applying the gray relational analysis method.After using ANOVA analysis according to the measured surface roughness and cutting force values,the most effective cutting parameter was observed to be the feed rate.In addition,the models for surface roughness and cutting force values were obtained with precisions of 99.63%and 99.68%,respectively.Effective wear mechanisms were found to be abrasion and adhesion.

GREY RELATIONAL ANALYSIS: A NEW STATISTICAL METHOD OF MULTIFACTORIAL ANALYSIS IN MEDICINE

The concept, fundamental theory, analytical steps and formulae of grey relational analysis (GRA)-a new statistical method or multifactorial analysis in the field of medicine were introduced. GRA of grouping sequence that is applied to medical study was built by the authors. An example was given to demonstrate it. The superiority of GRA was recounted briefly.

CAE-Based Robust Optimization for Deep-Drawing Process of Sheet Metal Forming Using Grey Relational Analysis Method

The theory of grey systems is a new technique for performing prediction, relational analysis and decision making in many areas. The grey relational analysis was used to optimize the deep-drawing process parameters with considerations of the multiple response （the wrinkle, crack and thinning variation）. The deep-drawing parame- ters, such as the blank holding force （Fhh）, the radii of punch and die （R1.R2）, the coefficients of friction （μ1,μ2,μ3） are considered. An orthogonal array is used for the experimental design. The multiple response values are ob- tained making use of finite element analysis （FEA）. Optimal process parameters are determined by the grey rela- tional grade obtained from the grey relational analysis for multi-performance characteristics （the wrinkle, crack and the thinning）. The analysis of variance （ANOVA） for the grey relational grade is implemented. The results show that the quality of stamped parts can be improved effectively through the new approach. The grey relational analysis can be applied in sheet metal forming.

An ideal point method adopting grey relational entropy to estimate life cycle cost with effectiveness of torpedo

To making the decision of the developing blue prints,ideal point method was selected to estimate the life cycle cost with effectiveness of torpedo.At the same time,the concept of grey relational entropy of the grey system theory was adopted to compute the distance between each blue print and the ideal point(or negative ideal point).The blue print,nearest to the ideal point and farthest to the negative ideal point,is the best one.As an example,four blue prints of torpedo were estimated.The result indicates the practical value of this method.

Priority-sequence of mineral resources' development and utilization based on grey relational analysis method

Generally, the sequence decision of the development and utilization of Chinese mineral resources is based on national and provincial overall plan of the mineral resources. Such plan usually cannot reflect the relative size of the suitability of the development and utilization of mineral resources. To solve the problem, the paper has selected the gift condition, the market condition, the technological condition,socio-economic condition and environmental condition as the starting-points to analyze the influential factors of the priority-sequence of mineral resources' development and utilization. The above 5 conditions are further specified into 9 evaluative indicators to establish an evaluation indicator system. At last,we propose a decision model of the priority sequence based on grey relational analysis method, and figure out the observation objects by the suitability index of development. Finally, the mineral resources of a certain province in China were analyzed as an example. The calculation results indicate that silver(2.0057), coal(1.9955), zinc(1.9442), cement limestone(1.9077), solvent limestone(1.5624) and other minerals in the province are suitable for development and utilization.

Optimizing SUS 304 wire drawing process by grey relational analysis utilizing Taguchi method

In the stainless steel 304 （SUS 304） wire drawing process, optimizing the die life and wire tensile strength, which are the larger-the-better quality characteristics （QCH） types, is of main interest. Three control factors, involving reduction ratio, lubricant temperature, and drawing speed, were investigated utilizing L9（34） orthogonal array （OA）. The grey relational analysis was conducted for the normalized signal-to-noise （S/N） ratios. The ordinal value of the grey grade was then used to decide optimal factor levels. The anticipated improvements in die life and wire tensile strength were estimated 25.31 h and 22.50 kg/mm2, respectively. To decide the significant factor which had effect on each QCH and predict the average value of each QCH, analysis of variance （ANOVA） was performed for S/N ratio and QCH. Confirmation experiments were then conducted, where a good overlap was noticed between the predicted and confirnation intervals for each QCH. The Hotelling T2 and the sample generalized variance control charts were finally utilized in controlling and monitoring future production. In conclusion, the grey relational analysis utilizing Taguchi method is an effective approach for optimizing the die life and wire tensile strength for SUS wire drawing process. 2008 University of Science and Technology Beijing. All rights reserved.