Journal of Engineering Research | |
Decision support system for the selection of advanced manufacturing technologies | |
Ateekh Ur-Rehman1  Shawkat Ali2  Abdulrahman M. Al-Ahmari3  | |
[1] Associate Professor, Department of Industrial Engineering,College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia;Former Teacher and Research Assistant, Department of Industrial Engineering,College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia;Professor, FARCAMT, Advanced Manufacturing Institute, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia. | |
关键词: Decision support system; fuzzy logics; multiple criteria; advanced manufacturing technology; | |
DOI : | |
学科分类:社会科学、人文和艺术(综合) | |
来源: Kuwait University * Academic Publication Council | |
【 摘 要 】
Advanced manufacturing technologies require huge capital investments and offer large number of intangible benefits such as flexibility, quality, competitiveness, customer satisfaction etc., which are ill structured in nature and sometimes very difficult to quantify. Here challenge is to incorporate full recognition of advanced manufacturing technologies benefits logically and accurately in justification model. In this paper, comprehensive decision support system approach is proposed to help manufacturing organizations in selecting advance manufacturing technology for investment, which is most suitable to their strategic objectives. In proposed model one can define more realistic value for benefits and sub benefits associated with a particular investment alternative. Proposed decision support system is based on fuzzy logic and assists decision makers of manufacturing firms in making more informed and complete analyses of alternative advanced manufacturing technologies. It opts both quantifiable and non-quantifiable benefit levels and sublevels for advanced manufacturing technologies. For non-quantifiable levels fuzzy linguistic approach is suggested. A case study is presented to test and demonstrate proposed decision support system.
【 授权许可】
Unknown
【 预 览 】
Files | Size | Format | View |
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RO201902028052318ZK.pdf | 775KB | download |