Six Sigma Project Selection Using the Hybrid Approach FAHP-FTOPSIS and Grey Relational Analysis Model

Valmohammadi, Changiz; Razi, Farshad Faezy; Einy, Fereidoun

doi:10.1109/emr.2021.3071368

Cited by 15 publications

(12 citation statements)

References 44 publications

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“…Author Year Method Fuzzy Sets S. Yao [10] 2021 AHP and VIKOR Triangular fuzzy Bakir and Atalik [11] 2021 AHP and MARCOS Triangular fuzzy Ilyas et al [7] 2021 BWM and TOPSIS -G. Taddese et al [8] 2021 AHP and VIKOR -Liu et al [12] 2021 TODIM and ELECTRE II Hesitant fuzzy Wanget al [31] 2021 AHP and TOPSIS Triangular fuzzy Valmohammadi et al [32] Notations: SWARA-stepwise weight assessment ratio analysis; WASPAS-weighted aggregated sum product assessment; CoCoSo-combined compromise solution; GIS-geographic information system; OWA-ordered weighted averaging.…”

Section: Nomentioning

confidence: 99%

“…To remedy this situation, the conversation results that are not consistent with the SFN should be adjusted by Euclidean normalization. By concatenating submatrices, the SF total influence matrix (𝐶 ̃) is formed, as shown in Equation (32).…”

Section: Linguisticmentioning

confidence: 99%

“…The SF direct-influence matrix is shown in Table A4. Based on that matrix, in step 4 and step 5, the SF total-influence matrix was determined according to Equations ( 25)- (32), as shown in Table A5. In step 6, as shown in Table 5, the defuzzied total influence matrix was formed according to Equation (14).…”

Section: Effectiveness Determination By Sfrdmamentioning

confidence: 99%

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A Composited Regret-Theory-Based Spherical Fuzzy Prioritization Approach for Moving High-Tech Manufacturing in Southeast Asia

2023

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After the pandemic, global supply chains will be in the process of restructuring. The relocation of production lines among countries is being considered for the purpose of sustainable development. The problem of determining the most suitable destination for manufacturers’ investments will become important, especially in the field of manufacturing high-tech products, which involves many complicated factors such as technological maturity, support policies, political issues, and technology security. In that context, Southeast Asia is seen as one of the regions attracting multinational manufacturers. To address this problem, a novel composited regret-theory-based spherical fuzzy prioritization approach is proposed. On the one hand, the super-efficiency slack-based model (super-SBM) of data envelopment analysis (DEA) is applied to evaluate efficiency, based on indicators. On the other hand, the novel spherical fuzzy regret-theory-based decision-making approach (SfRDMA) is developed and introduced to determine effectiveness, based on criteria. Then, the efficiency and the effectiveness of countries are combined by a composite-score function that is based on a geometric mean and an arithmetic mean. The findings imply that government policy, political stability, and human resources availability are the three most important criteria. Moreover, India, Thailand, Vietnam, Malaysia, and Indonesia are identified as promising destinations for the world’s high-tech production lines.

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Section: Nomentioning

confidence: 99%

Section: Linguisticmentioning

confidence: 99%

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A Composited Regret-Theory-Based Spherical Fuzzy Prioritization Approach for Moving High-Tech Manufacturing in Southeast Asia

2023

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“…In order to meet the market demand and the economic benefits of enterprises, Valmohammadi et al studied the introduction of the fuzzy analytic hierarchy process to determine the Shima project and ranked the projects in the scheme with the help of the fuzzy grey correlation method. e results show that the DSS system of the project can effectively improve the performance of the production process and organization process [8]. In order to improve the accuracy of decision-making and reduce the subjective error of expert judgment, Uluta introduces fuzzy set theory to build a composite fuzzy multicriteria decision-making model, ranks and fuzzy expands the weight value of the index, and applies it to a practical case [9].…”

Section: Related Workmentioning

confidence: 99%

Research on Performance Management Evaluation of Public Sports Venues Based on GFAHP

et al. 2022

Mathematical Problems in Engineering

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The importance of public stadiums has become increasingly prominent, but the efficiency of its performance management operation mechanism is low, which affects the overall operation efficiency of the whole stadium. However, due to the diversity and incompleteness of its data types, the traditional analytic hierarchy process is difficult to construct its index system. This article introduces the grey fuzzy analytic hierarchy process. Based on the analysis of its performance management problems, this article constructs the index system and makes an application case analysis. The results show that the GFAHP method (group fuzzy analytic hierarchy process) can ensure the integrity of information data. In data classification, the highest accuracy of sample classification is 40.13%, and the relative error rate is basically less than 6%. The performance effect is much higher than other classification algorithms. At the same time, the total score of the evaluation index system constructed by GFAHP is more than 3, the overall operation is good, and the risk evaluation effect of each influencing index factor is also good. Using the grey analytic hierarchy process to evaluate the operation and performance management of public stadiums and gymnasiums will help managers do a good job in risk control and quality dynamic adjustment, so as to improve the operation efficiency and benefit of stadiums and gymnasiums.

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“…The GIA is commonly used for solving problems in engineering (Kokocińska et al ., 2020), natural and social sciences (Nowak et al ., 2020). Example applications of GIA models in the recent years include: service quality analysis in healthcare (Javed and Liu, 2018), the Industry 4.0 research (Fahim et al ., 2021), green supplier selection (Quan et al ., 2018), project management (Javed and Liu, 2019), grain production (Zhang et al ., 2021), research on the effect of electrification on the level of economic development (Nowak et al ., 2021), research on the development of science and technology (Wei and Wu, 2016), research on sustainable development (Yi et al ., 2021; Kaswan and Rathi, 2021), research on social media (Weng et al ., 2021), research on customer satisfaction (Peng et al ., 2021; Xiang, 2022), business performance analysis (Škrinjarić and Šego, 2021; Ellibeş and Candan, 2021), corporate social responsibility analysis (Diaz and Nguyen, 2021), quality management (Valmohammadi et al ., 2021), or financial management (Ramezani, 2022). In general terms, within the relational analysis in the grey system theory, we distinguish distance-, surface-, and panel-based models (Liu et al.…”

Section: Introductionmentioning

confidence: 99%

The evaluation of grey relative incidence

Nowak,

Pawłowska-Nowak,

Kokocińska

et al. 2023

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PurposeWith the use of the grey incidence analysis (GIA), indicators such as the absolute degree of grey incidence (εij), relative degree of grey incidence (rij) or synthetic degree of grey incidence (ρij) are calculated. However, it seems that some assumptions made to calculate them are arguable, which may also have a material impact on the reliability of test results. In this paper, the authors analyse one of the indicators of the GIA, namely the relative degree of grey incidence. The aim of the article was to verify the hypothesis: in determining the relative degree of grey incidence, the method of standardisation of elements in a series significantly affects the test results.Design/methodology/approachTo achieve the purpose of the article, the authors used the numerical simulation method and the logical analysis method (in order to draw conclusions from our tests).FindingsIt turned out that the applied method of standardising elements in series when calculating the relative degree of grey incidence significantly affects the test results. Moreover, the manner of standardisation used in the original method (which involves dividing all elements by the first element) is not the best. Much more reliable results are obtained by a standardisation that involves dividing all elements by their arithmetic mean.Research limitations/implicationsLimitations of the conducted evaluation involve in particular the limited scope of inference. This is since the obtained results referred to only one of the indicators classified into the GIA.Originality/valueIn this article, the authors have evaluated the model of GIA in which the relative degree of grey incidence is determined. As a result of the research, the authors have proposed a recommendation regarding a change in the method of standardising variables, which will contribute to obtaining more reliable results in relational tests using the grey system theory.

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Six Sigma Project Selection Using the Hybrid Approach FAHP-FTOPSIS and Grey Relational Analysis Model

Cited by 15 publications

References 44 publications

A Composited Regret-Theory-Based Spherical Fuzzy Prioritization Approach for Moving High-Tech Manufacturing in Southeast Asia

A Composited Regret-Theory-Based Spherical Fuzzy Prioritization Approach for Moving High-Tech Manufacturing in Southeast Asia

Research on Performance Management Evaluation of Public Sports Venues Based on GFAHP

The evaluation of grey relative incidence

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