The presented state of the art as well as the practical circumstances lead to maintenance systems where one
standard strategy (i.e. predictive maintenance) is followed. Regarding the case of offshore wind turbines for
instance, a yearly inspection with an extensive maintenance plan is used to ensure the predictive recognition of
future faults. Nevertheless, failures often lead to downtimes of the system and to troubleshooting with corrective
measures. Moreover, the monitoring of the technical condition of systems or components by sensor technology
generally just enables the assessment of a subset of data that would be needed for a holistic perspective.
Regarding the methodological basics and the main concept of the so-called “preacting” maintenance approach,
the fundamental level is still based on condition monitoring and data processing. Besides the technical perspective,
economic data (e.g. historical data of the maintenance measures) or environmental data (like weather in the case of
offshore wind turbines) have to be considered. Condition monitoring and data processing will lead to a deep
understanding of the current condition of technical systems. Hereby, they achieve the general ability to inquire
maintenance tasks related to their particular requirements.
Based on that, the preactive paradigm includes three further objectives of traditional maintenance strategies.
Corrective maintenance tasks or troubleshooting are supported by recognition of failures at an early stage so that
planning and controlling as well as scheduling of tasks and according resources are enabled. Moreover, preventive
maintenance is followed for some components essentially with a linear wear-out curve. Those tasks should be
assessed under cost-/risk considerations. Economic effects take place in case those preventive tasks are scheduled
together with other ones (e.g. troubleshooting). Finally, the maintenance and inspection based on fixed intervals can
be continued, which is not typical for general condition-based approaches. Data and information derived from the
previous described basis should enable dynamic maintenance and inspection scopes according to the particular
condition or requirements of considered technical systems. From the methodical perspective, data and information
have to be processed in order to schedule operative executions of maintenance measures according to the following
assumptions: