AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (266.1 KB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline

Fuzzy Multiple Attribute Decision Making for Evaluating Aggregate Risk in Green Manufacturing

Hua LIUWeiping CHEN( )Zhixin KANGTungwai NGAIYuanyuan LI
College of Mechanical Engineering, South China University of Technology, Guangzhou 510640, China
Show Author Information

Abstract

Industrial risk and the diversification of risk types both increase with industrial development. Many uncertain factors and high risk are inherent in the implementation of new green manufacturing methods. Because of the shortage of successful examples and complete and certain knowledge, decision-making methods using probabilities to represent risk, which need many examples, cannot be used to evaluate risk in the implementation of green manufacturing projects. Therefore, a fuzzy multiple attribute decision-making (FMADM) method was developed with a three-level hierarchical decision-making model to evaluate the aggregate risk for green manufacturing projects. A case study shows that the hierarchical decision-making model of the aggregate risk and the FMADM method effectively reflect the characteristics of the risk in green manufacturing projects.

References

【1】
【1】
 
 
Tsinghua Science and Technology
Pages 627-632

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
LIU H, CHEN W, KANG Z, et al. Fuzzy Multiple Attribute Decision Making for Evaluating Aggregate Risk in Green Manufacturing. Tsinghua Science and Technology, 2005, 10(5): 627-632. https://doi.org/10.1016/S1007-0214(05)70130-9

2

Views

0

Downloads

0

Crossref

N/A

Web of Science

0

Scopus

0

CSCD

Received: 01 March 2004
Revised: 20 December 2004
Published: 01 October 2005
© Tsinghua University Press 2005