Due to the European Union renewable energy targets for 2030 and beyond, increasing trends of installed offshore wind energy production capacity and increasing wind turbine size emerge. Therefore, the offshore wind maintenance demand increases and becomes increasingly more complex. The most applied maintenance strategy is reliability-centred maintenance, which is a form of preventive maintenance that uses prediction models to determine future ocean and weather states and asset health states. Based on those predictions, maintenance demand is scheduled. The processes that lead up to the generation of the maintenance schedule ranging from asset condition monitoring, to data analysis, to future state predictions, to maintenance scheduling are currently highly automated. The last part of the maintenance organisation cycle, matching and contracting of maintenance supply for the demand is currently still done manually via email and phone. Offshore wind maintenance operations predominantly are multi-party operations, requiring vessels, teams of technicians, spare-parts and ports supplied by the WPP itself, shared WPP inventory, third-party service providers and OEMs. The increasing maintenance demand puts a lot of pressure on the already complex task of the Asset Manager that is processing all this information and communication manually.
The problem that is preventing automation of the matching and contracting process, is the lack of a system of demand and supplier systems, that processes commercially sensitive information, such as maintenance demand schedules and supplier availability schedules, in a trustworthy privacy preserving manner. The main research question for this design research therefore becomes:
How to design a technical feasible decentralized system-of-systems that enables automated matching and contracting of maintenance supply for scheduled demand through privacy preserving processing of commercially sensitive data?...