首页 | 本学科首页   官方微博 | 高级检索  
     


Turbofan aero-engine efficiency evaluation: An integrated approach using VSBM two-stage network DEA
Affiliation:1. Aristotle University of Thessaloniki, School of Economic Sciences, MSc Programme in Logistics and Supply Chain Management, University Campus, Thessaloniki 54124, Greece;2. NATO Communications and Information Agency (NCIA), Boulevard Leopold III, Brussels 1110 Belgium;3. University of Macedonia, School of Information Sciences, Department of Applied Informatics, Information Systems and e-Business Laboratory (ISeB), 156 Egnatia Str., Thessaloniki 54636, Greece
Abstract:The application of Data Envelopment Analysis (DEA) has been wide, especially for the purpose of evaluating efficiency among similar production processes within enterprises belonging to particular industries. Although research pertinent to DEA has primarily focused on efficiency of production systems or corporate entities/organizations (e.g., terminals, hospitals, universities/schools, banks), fairly little attention has been given to efficiency evaluation among engineering systems featuring common configurations (e.g., automobiles, power plants). Furthermore, the limited previous literature involving efficiency evaluation of engineering systems has implemented DEA methodologies with limited discriminative power, i.e. there is a quite increased portion of efficient Decision Making Units (DMUs). In the current paper, a methodological framework deploying Variable intermediate measures Slacks-Based Measure (VSBM) Two-Stage Network DEA is implemented, in order to evaluate the efficiency of turbofan aero-engines, currently utilized by active-duty commercial and military aircraft. Apart from exploring the positive correlation of DEA efficiency with engineering efficiency, we also develop a methodology evaluating the features of near-future turbofan designs in terms of DEA efficiency, thus comprising a potential tool for efficiency assessment of any turbofan aero-engine being in the conceptual or preliminary design stage.
Keywords:
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号