The technological feasibility of a condition-based maintenance (CBM) policy is intrinsically related to the suitable selection of condition monitoring (CM) technologies such as vibration- and oil analysis or other non-destructive testing (NDT) techniques such as radiographic- and magnetic particle testing. However, in practice the selection can be quite complex due to the tremendous number of variables that need to be taken into account. These variables can be classified into three categories: (1) variables that are inherently related to the features of the system to be monitored (e.g. material composition, geometry and motion); (2) variables that are related to the supposedly selected CM technology(-ies) (e.g. physical limitations and diagnostic capabilities); and (3) variables that are related to the failure mechanism under which the system predominantly fails (e.g. corrosion, wear and fatigue). Finding the optimum combination of these variables, with the aim of selecting the most suitable CM technology(-ies), is the objective of the decision support system (DSS) presented in this thesis.
|Award date||28 Mar 2018|
|Place of Publication||Enschede|
|Publication status||Published - 28 Mar 2018|