• DocumentCode
    3728876
  • Title

    Dynamic risk modeling and assessing in maintenance outsourcing with FCM

  • Author

    Afshin Jamshidi;Samira Abbasgholizadeh Rahimi;Daoud Ait-kadi;Angel Ruiz

  • Author_Institution
    Department of Mechanical Engineering, Universit? Laval, avenue de la M?decine, G1V0A6, Quebec, Canada
  • fYear
    2015
  • Firstpage
    209
  • Lastpage
    215
  • Abstract
    Maintenance outsourcing is a common practice in many industries, such as aviation and medical equipment manufacturing. However, there is always some dynamic risks associated with outsourcing. Risk analysis of maintenance outsourcing projects is a complex task due to consisting of many risk factors with dependencies among them. Although there are some studies on maintenance outsourcing risks, no attention has been paid to the risk analysis of maintenance outsourcing by considering the dependencies among risk factors. Considering the dependencies among risk factors could lead to more precise risks analysis and increase the success rate of outsourcing projects. To address this, we are proposing an advanced decision support tool called “Fuzzy Cognitive Maps” (FCM) which can deal with risks of such complicated systems. FCM represents the behavior of complex systems accurately and is able to consider uncertainties, imprecise information, the interactions between risk factors, information scarcity, and several decision maker´s opinions. In addition, it could be applied in different decision makings problems related to outsourcing projects such as provider selection problem. Therefore, the proposed tool would help practitioners to manage maintenance outsourcing risks in a more effective and proactive way and offer better risk mitigation solutions.
  • Keywords
    "Outsourcing","Maintenance engineering","Risk management","Algorithm design and analysis","Organizations"
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Systems Management (IESM), 2015 International Conference on
  • Type

    conf

  • DOI
    10.1109/IESM.2015.7380159
  • Filename
    7380159