Using data to predict the best moments to perform maintenance on systems and machines, that is -smart maintenance-. Smart maintenance can drastically reduce maintenance costs and make systems more reliable. In several research projects, the University of Twente and the Netherlands Defence Academy are going to expand their joint smart maintenance research substantially.
Prof. Tiedo Tinga, professor at both UT and the Netherlands Defence Academy, explains. -We have been researching this subject for a long time, for application in wind turbines, railways and the manufacturing industry. The focus in the new projects is on the maritime sector in particular, on maintenance in both the navy and merchant shipping.- Developing new methods of converting data into usable information should make it possible to predict future breakdowns in ships. The aim is to automate a lot of the data acquisition.
Complex situationShips are complex systems. As there are so many different components and subsystems that can malfunction, it is hard to make accurate predictions. And making maintenance forecasts for an entire fleet is even more complex. Those maintenance choices are made generally on the basis of experience or simply at fixed intervals. A better understanding of this can be obtained by simulating variable use, changing situations and deterioration of systems in scientific models. Those models are subsequently combined with artificial intelligence and better IT systems for collecting and sharing data. This will enable the sector to base the maintenance schedule for its fleets on data instead of on experience or instinct.
Corrosion damageIn one of the research projects the researchers are going to examine one of the biggest cost factors, corrosion. Electrochemical measurements ought to make it possible to monitor and ultimately predict the degree of corrosion damage to a ship’s hull. Some coatings age more quickly than others, which currently makes accurate forecasting difficult.
New machinesThe two parties are also going to research new systems for which little is yet known about the maintenance cycles. For instance, the focus of one of the research projects is on a new sustainable propulsion technique for ships: AmmoniaDrive. In that project, ammonia is used as an energy source and converted into electricity by fuel cells. It is not yet known how long such a system will last and in what ways the system could break down.
The aforementioned research comprises five different research projects: European Digital Naval Foundation (EDINAF), digital ship sTructural Health mOnitoRing (dTHOR) (both part of the European Defence Fund), AmmoniaDrive, Ship Life Cycle Management (SILICA) and DTP Data-Driven Smart Maintenance. Prof. Tiedo Tinga is Professor of Dynamics Based Maintenance at the Mechanics of Solids, Surfaces & Systems department ( MS3 ; Faculty of Engineering Technology ) and Professor of Life Cycle Management at the Netherlands Defence Academy.