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  • 标题:Model for a Predictive Maintenance System Effectiveness Using the Analytical Hierarchy Process as Analytical Tool
  • 本地全文:下载
  • 作者:Rahul Baidya ; Rahul Baidya ; Sadhan Kumar Ghosh
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2015
  • 卷号:48
  • 期号:3
  • 页码:1463-1468
  • DOI:10.1016/j.ifacol.2015.06.293
  • 语种:English
  • 出版社:Elsevier
  • 摘要:Abstract Proper maintenance can enhance the productivity of the company and increases its value in the market. This paper addresses the issue of selecting an effective maintenance technology considering the strategic maintenance and managerial policy of an organization. The research proposes a model frame work for predictive maintenance indicator effectiveness (PMIE) based on the analytical hierarchy process (AHP). The study was done considering three case studies. Firstly a questioner survey was carried out for primary research, secondly a model was developed and thirdly the data were analyzed using the developed model. The main study provided a robust model which can gauge the strategically important available technology and can exclude the out dated or/ and inappropriate technology. There are many researches in this field where number of models were proposed like the maintenance management system, maintenance performance measurement and maintenance performance indicators but the details of the predictive maintenance indicator effectiveness specifically based on condition based maintenance (CBM) with emphasizing on the major strategic maintenance and managerial requirements using analytical hierarchy process (AHP) is hardly available in the literature.
  • 关键词:KeywordsPredictive MaintenanceMaintenance StrategyCondition Based MaintenanceAHP
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