Evaluation of vehicle fleet maintenance management indicators by application of DEMATEL and ANP
- 作者：Davor Vujanovi膰 ; d.vujanovic@sf.bg.ac.rs ; Vladimir Mom膷ilovi膰 ; Neboj&scaron ; a Bojovi膰 ; Vladimir Papi膰
- 关键词：Maintenance management ; Vehicle fleets ; Energy efficiency ; Multiple Criteria Decision-Making (MCDM) ; Decision Making Trial and Evaluation Laboratory (DEMATEL) ; Analytic Network Process (ANP)
- 刊名：Expert Systems with Applications
- 出版年：2012
- 期刊代码：62_09574174
- 类别：et
- 出版时间：15 September, 2012
- 卷：39
- 期：12
- 页码：10552-10563
- 文件大小：708 K
摘要
The paper refers to the importance of maintenance management to increase the vehicle fleet energy efficiency. The fleet maintenance management influences as the vehicle maintenance process itself as well as the primary transport process but also their environment. In order to increase fleet energy efficiency by means of a more efficient maintenance management, it is indispensable to observe maintenance process, transport process and the environment. Since the implementation effects of such measures can be measured by different indicators, this paper analyses the influence of indicators in all three mentioned areas on management decision-making. In this sense, appropriate indicators have been defined and subsequently used in fleet maintenance management. To determine levels and intensities of interdependence as well as relative weight of selected indicators two methods have been combined: Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP). A model was proposed with indicators鈥?interdependence whose relative weights were calculated. The proposed model has been implemented in several companies with road vehicle fleets. Collected results show the perceived evaluation by company managers in view of maintenance management process influence onto their fleet energy efficiency. Besides, by proposed model implementation we have obtained equally managers鈥?evaluation upon effectiveness and efficiency of the maintenance management within studied companies.