Search results

1 – 10 of 385
Article
Publication date: 29 July 2020

Xiumei Hao, Mingwei Li and Yuting Chen

This paper takes the seven overcapacity industries such as the textile industry, electricity and heat, steel, coal, automobile manufacturing, nonferrous metals and petrochemical…

Abstract

Purpose

This paper takes the seven overcapacity industries such as the textile industry, electricity and heat, steel, coal, automobile manufacturing, nonferrous metals and petrochemical industry as research objects and proposes a TOPSIS grey relational projection group decision method with mixed multiattributes, which is used for the ranking of the seven industries with overcapacity and provided relevant departments with a basis for decision-making.

Design/methodology/approach

First, an evaluation index system from four aspects is established. Secondly, the attributes of linguistic information are converted into two-dimensional interval numbers and triangular fuzzy numbers, and an evaluation matrix is constructed and normalized. This paper uses the AHP method to determine the subjective weights and uses the coefficient of variation method to determine the objective weights. Moreover, this paper sets up the optimization model with the largest comprehensive evaluation value to determine the combined weights. Finally, the TOPSIS grey relational projection method is proposed to calculate the closeness of grey relational projections and to rank them.

Findings

This paper analyzes the problem of overcapacity in seven industries with the TOPSIS grey relational projection method. The results show that the four industries of automobile manufacturing, textile, coal and petrochemical are all in serious overcapacity levels, while the three industries of steel, nonferrous metals and electric power are relatively in weak overcapacity level in the three years of 2016–2018. TOPSIS grey relational projection method ranks the overcapacity degree of the seven major overcapacity industries, making the relative overcapacity degree of each industry more clear and providing a reference for the government to formulate targeted policies and measures for each industry.

Practical implications

By using TOPSIS grey relational projection method to evaluate the overcapacity of the seven major overcapacity industries, on the one hand, it makes the relative overcapacity degree of each industry more clear, on the other hand, it can provides the basis for the government and decision-making departments. This helps them promote better the healthy and orderly economic development of the seven major industries and avoid resource waste caused by overcapacity.

Originality/value

This article solves the single evaluation method caused by the limited indicators in the past, combines TOPSIS and the grey relational projection method and applies it to the overcapacity evaluation of the industry, not only applies it to the evaluation of overcapacity for the first time but also involves novel problems and methods, which expands the scope of application of the model.

Details

Grey Systems: Theory and Application, vol. 11 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 6 September 2018

Dang Luo, Lili Ye, Yanli Zhai, Hanyu Zhu and Qicun Qian

Hazard assessment on drought disaster is of great significance for improving drought risk management. Due to the complexity and uncertainty of the drought disaster, the index…

Abstract

Purpose

Hazard assessment on drought disaster is of great significance for improving drought risk management. Due to the complexity and uncertainty of the drought disaster, the index values have some grey multi-source heterogeneous characteristics. The purpose of this paper is to construct a grey projection incidence model (GPIM) to evaluate the hazard of the drought disaster characterised by the grey heterogeneity information.

Design/methodology/approach

First, the index system of the drought hazard risk is established based on the formation mechanism of the drought disaster. Then, the GPIM for the heterogeneous panel data is constructed to assess drought hazard of five cities in Henan Province. Subsequently, based on the assessment results, the grey clustering model is employed for the regional division.

Findings

The findings demonstrate that five cities in central Henan Province are divided into three categories, which correspond to three different risk grades, respectively. With respect to different drought risk areas, corresponding countermeasures and suggestions are proposed.

Practical implications

This paper provides a practical and effective new method for the hazard assessment on drought disaster. Meanwhile, these countermeasures and suggestions can help policy makers to improve the efficiency of drought resistance work and reduce the losses caused by drought disasters in Henan Province.

Originality/value

This paper proposes a new GPIM which resolves the assessment problems of the uncertain systems with grey heterogeneous information, such as real numbers, interval grey numbers and three-parameter interval grey numbers. It not only expands the application scope of the grey incidence model, but also enriches the research of panel data.

Details

Grey Systems: Theory and Application, vol. 8 no. 4
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 23 September 2019

Bingjun Li and Xiaoxiao Zhu

The purpose of this paper is to put forward the grey relational decision-making model of three-parameter interval grey number based on Analytic Hierarchy Process (AHP) and Data…

Abstract

Purpose

The purpose of this paper is to put forward the grey relational decision-making model of three-parameter interval grey number based on Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA), based on the previous study of grey relational decision-making model, and it considers the advantages of the decision-making schemes and the subjective preferences of decision makers.

Design/methodology/approach

First of all, through AHP, the preference of each index is analyzed and the index weight is determined. Second, the DEA model is adopted to obtain the index weight from the perspective of the most beneficial to each scheme and objectively reflect the advantages of different schemes. Then, assign the comprehensive weights to each index of the grey relational decision-making model of three-parameter interval grey number, and calculate the grey relation degree of each scheme to rank the schemes.

Findings

The effectiveness of the model is proved by an example of carrier aircraft selection.

Practical implications

The applicability of this model is analyzed by taking carrier aircraft selection as an example. In fact, this model can also be widely used in agriculture, industry, economy, society and other fields.

Originality/value

In this paper, the combination of AHP and DEA is used to determine the index weight. Based on which, the grey relation degree under the three-parameter interval grey number is calculated. It intended the application space of the grey relational decision-making model.

Details

Grey Systems: Theory and Application, vol. 10 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 7 August 2019

Bobby Oedy Pramoedyo Soepangkat, Rachmadi Norcahyo, Pathya Rupajati, Mohammad Khoirul Effendi and Helena Carolina Kis Agustin

The purpose of this paper is to investigate prediction and optimization of multiple performance characteristics in the wire electrical discharge machining (wire-EDM) process of…

Abstract

Purpose

The purpose of this paper is to investigate prediction and optimization of multiple performance characteristics in the wire electrical discharge machining (wire-EDM) process of SKD 61 (AISI H13) tool steel.

Design/methodology/approach

The experimental studies were conducted under varying wire-EDM process parameters, which were arc on time, on time, open voltage, off time and servo voltage. The optimized responses were recast layer thickness (RLT), surface roughness (SR) and surface crack density (SCD). Arc on time was set at two different levels, whereas the other four parameters were set at three different levels. Based on Taguchi method, an L18 mixed-orthogonal array was selected for the experiments. Further, three methods, namely grey relational analysis (GRA), backpropagation neural network (BPNN) and genetic algorithm (GA), were applied separately. GRA was performed to obtain a rough estimation of optimum drilling parameters. The influences of drilling parameters on multiple performance characteristics were determined by using percentage contributions. BPNN architecture was determined to predict the multiple performance characteristics. GA method was then applied to determine the optimum wire-EDM parameters.

Findings

The minimum RLT, SR and SCD could be obtained by setting arc on time, on time, open voltage, off time and servo voltage at 2 ms, 3 ms, 90 volt, 10 ms and 38 volt, respectively. The experimental confirmation results showed that BPNN-based GA optimization method could accurately predict and significantly improve all of the responses.

Originality/value

There were no publications regarding multi-response optimization using a combination of GRA and BPNN-based GA methods during wire-EDM process available.

Details

Multidiscipline Modeling in Materials and Structures, vol. 15 no. 5
Type: Research Article
ISSN: 1573-6105

Keywords

Article
Publication date: 24 December 2021

Li Li and Xican Li

In order to make grey relational analysis applicable to the interval grey number, this paper discusses the model of grey relational degree of the interval grey number and uses it…

Abstract

Purpose

In order to make grey relational analysis applicable to the interval grey number, this paper discusses the model of grey relational degree of the interval grey number and uses it to analyze the related factors of China's technological innovation ability.

Design/methodology/approach

First, this paper gives the definitions of the lower bound domain, the value domain, the upper bound domain of interval grey number and the generalized measure and the generalized greyness of interval grey number. Then, based on the grey relational theory, this paper proposes the model of greyness relational degree of the interval grey number and analyzes its relationship with the classical grey relational degree. Finally, the model of greyness relational degree is applied to analyze the related factors of China's technological innovation ability.

Findings

The results show that the model of greyness relational degree has strict theoretical basis, convenient calculation and easy programming and can be applied to the grey number sequence, real number sequence and grey number and real number coexisting sequence. The relational order of the four related factors of China's technological innovation ability is research and development (R&D) expenditure, R&D personnel, university student number and public library number, and it is in line with the reality.

Practical implications

The results show that the sequence values of greyness relational degree have large discreteness, and it is feasible and effective to analyze the related factors of China's technological innovation ability.

Originality/value

The paper succeeds in realizing both the model of greyness relational degree of interval grey number with unvalued information distribution and the order of related factors of China's technological innovation ability.

Details

Grey Systems: Theory and Application, vol. 12 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 26 October 2012

Hong‐fa Ke, Hong‐Mei Du, Ke He and Xiao‐Hong Yu

The purpose of this paper is to solve the comprehensive evaluation of the equipment maintainability level based on grey system theory, and make an analysis of the corresponding…

412

Abstract

Purpose

The purpose of this paper is to solve the comprehensive evaluation of the equipment maintainability level based on grey system theory, and make an analysis of the corresponding influencing factors and their prioritization process.

Design/methodology/approach

Considering the diversity, uncertainty and small sample size of the influencing factors of the equipment maintainability level, a multilayer evaluation attribute system is set up, and the grey relational method is utilized to assess the equipment's comprehensive maintainability. First, the bottom layer relational coefficient and weighted relational degree are analyzed, and, by means of the focus of relational degree through the bottom layer to top layer, the general evaluation of the equipment maintainability is carried out. Second, the equipment maintainability level and its influencing factors model, i.e. GM(1,N) model are set up, and the prioritization of the influencing factors is achieved through the comparison of the size of the model drive coefficients. Finally, the practical example calculation results show that this method has not only realized a sensible and effective evaluation of the equipment maintainability level, but also provided a prioritization of the influencing factors, which helps to focus attention on the major influencing factors and make this method of significant engineering application value in the improvement of the equipment maintainability level.

Findings

The modeling of electronic equipment maintainability level and analysis of its corresponding practical example prove that grey system theory could not only perform a comprehensive evaluation of the equipment maintainability level, but also provide a quantitative analysis of its various influencing factors, whereas, other methods such as fuzzy mathematics, etc. can only make a general evaluation of the equipment maintainability level.

Practical implications

This paper has realized an integral evaluation of the equipment maintainability level and has made an analysis of the prioritization of its various influencing factors. These investigation results could be introduced as a promising innovative idea in the evaluation of the equipments' other performances and the prioritization of its various corresponding influencing factors.

Originality/value

Considering the diversity and uncertainty of influencing factors of the equipment maintainability level, this paper has realized a multilayer evaluation attribute system to perform a comprehensive evaluation of equipment maintainability level by means of weighted grey relational degree model. Furthermore, the prioritization of its various influencing factors is achieved based on the GM(1,N) model.

Details

Grey Systems: Theory and Application, vol. 2 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 6 February 2017

Miraç Eren and Selahattin Kaynak

The purpose of this paper is to investigate the multi-period, multi-attribute decision-making problems that arise when the information required to make decisions is provided at…

Abstract

Purpose

The purpose of this paper is to investigate the multi-period, multi-attribute decision-making problems that arise when the information required to make decisions is provided at different periods.

Design/methodology/approach

For the multi-period grey relational analysis (MP-GRA) procedure, the time dimension is added to the grey relational analysis algorithm, which is a multi-attribute decision analysis that has been developed. As a case study to test the functionality and applicability of the model, 28 European Union member states were ranked by the MP-GRA method developed according to their human development and global competitiveness variables for the years 2006-2015.

Findings

The general ranking of EU member states has been provided in intervals of certain time periods called decision units.

Originality/value

Another dimension based on time periods has been added to a ranking technique. This case also shows that the opinions of decision-makers may be added separately to enhance evaluations.

Details

Grey Systems: Theory and Application, vol. 7 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 2 November 2015

Shervin Zakeri and Mohammad Ali Keramati

Supplier selection is a complex multiple criteria decision (MCDM) problem which directly depends on decision makers’ choice. Some decisions are getting involved with linguistic…

Abstract

Purpose

Supplier selection is a complex multiple criteria decision (MCDM) problem which directly depends on decision makers’ choice. Some decisions are getting involved with linguistic variables and they are not mathematically operable. To solve a typical decision problem through MCDM techniques, a number or a numerical interval should be defined. The purpose of this paper is to focus on that numerical interval and in a case of supplier selection, the aim is to close the decisions to the real number that the decision maker mentions and this number is in a numerical interval.

Design/methodology/approach

The proposed method deals with grey relational analysis (GRA) and develops it by applying triangular fuzzy numbers. The grey numbers have two defined bounds; the proposed method defines two fuzzy bounds for each grey attribute. In the proposed method, the fuzzy membership function has been employed for each bounds of grey attribute to make them to fuzzy bounds with two undefined bounds. Also to make comparison, with employing of TOPSIS technique, both of the grey fuzzy combination decision matrix and the original grey decision matrix are obtained.

Findings

The results indicate that, except to the ideal solutions, the grey relation coefficient for each alternative is too close to each other. Indeed, they are too close to zero. Applying the proposed method in problem of supplier selection shows the difference between two selected supplier in proposed method and the original grey method.

Originality/value

As mentioned heretofore this paper aims to make decision makers’s decision more accurate and actually there is no other researches which used this combination method.

Details

Grey Systems: Theory and Application, vol. 5 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 24 August 2018

Eduardo Guilherme Satolo, Caroline Leite, Robisom Damasceno Calado, Gustavo Antiqueira Goes and Douglas D’Alessandro Salgado

The lean production system and world class manufacturing (WCM) have been prominent in recent studies due to their conceptual synergy. However, although the number of studies is…

Abstract

Purpose

The lean production system and world class manufacturing (WCM) have been prominent in recent studies due to their conceptual synergy. However, although the number of studies is increasing, the research is immature, especially regarding the interaction between topics. Therefore, the purpose of this paper is to rank the tools of the lean production system, indicating how they help organizations achieve WCM, using the theory of grey systems.

Design/methodology/approach

Therefore, the authors conducted an initial survey to collect data to determine how the lean production tools are related to the WCM pillars. These data were analyzed by the grey relational analysis statistical method, which passes through the construction of four stages.

Findings

The results show that of the lean production tools, stream mapping, kaizen, total productive maintenance, Six Sigma, standardized work and 5S stand out for their use and implementation in the organizational environment and facilitate organizations’ transitions to world-class performance through the WCM pillars.

Practical implications

The results achieved guide organizations to use the tools of the lean production system to help them reach world class status.

Originality/value

This paper stands out in the field of operations management, specifically in the research on lean production, by making use of the theory of grey correlation system in an innovative and original way. In addition, it promotes the consolidation of information on two of the main administrative strategies currently employed in the organizational environment.

Details

Grey Systems: Theory and Application, vol. 8 no. 4
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 5 April 2019

Mohamad Amin Kaviani, Amir Karbassi Yazdi, Lanndon Ocampo and Simonov Kusi-Sarpong

The oil and gas industry is a crucial economic sector for both developed and developing economies. Delays in extraction and refining of these resources would adversely affect…

Abstract

Purpose

The oil and gas industry is a crucial economic sector for both developed and developing economies. Delays in extraction and refining of these resources would adversely affect industrial players, including that of the host countries. Supplier selection is one of the most important decisions taken by managers of this industry that affect their supply chain operations. However, determining suitable suppliers to work with has become a phenomenon faced by these managers and their organizations. Furthermore, identifying relevant, critical and important criteria needed to guide these managers and their organizations for supplier selection decisions has become even more complicated due to various criteria that need to be taken into consideration. With limited works in the current literature of supplier selection in the oil and gas industry having major methodological drawbacks, the purpose of this paper is to develop an integrated approach for supplier selection in the oil and gas industry.

Design/methodology/approach

To address this problem, this paper proposes a new uncertain decision framework. A grey-Delphi approach is first applied to aid in the evaluation and refinement of these various available criteria to obtain the most important and relevant criteria for the oil and gas industry. The grey systems theoretic concept is adopted to address the subjectivity and uncertainty in human judgments. The grey-Shannon entropy approach is used to determine the criteria weights, and finally, the grey-EDAS (evaluation based on distance from average solution) method is utilized for determining the ranking of the suppliers.

Findings

To exemplify the applicability and robustness of the proposed approach, this study uses the oil and gas industry of Iran as a case in point. From the literature review, 21 criteria were established and using the grey-Delphi approach, 16 were finally considered. The four top-ranked criteria, using grey-Shannon entropy, include warranty level and experience time, relationship closeness, supplier’s technical level and risks which are considered as the most critical and influential criteria for supplier evaluation in the Iranian oil and gas industry. The ranking of the suppliers is obtained, and the best and worst suppliers are also identified. Sensitivity analysis indicates that the results using the proposed methodology are robust.

Research limitations/implications

The proposed approach would assist supply chain practicing managers, including purchasing managers, procurement managers and supply chain managers in the oil and gas and other industries, to effectively select suitable suppliers for cooperation. It can also be used for other multi-criteria decision-making (MCDM) applications. Future works on applying other MCDM methods and comparing them with the results of this study can be addressed. Finally, broader and more empirical works are required in the oil and gas industry.

Originality/value

This study is among the first few studies of supplier selection in the oil and gas industry from an emerging economy perspective and sets the stage for future research. The proposed integrated grey-based MCDM approach provides robust results in supplier evaluation and can be used for future domain applications.

1 – 10 of 385