Developing a model to minimize repair dwell time based on condition monitoring system for major engine failure warning

Major engine failure may result in unwanted and unpredictable huge amounts of loss of income for the shipping companies. When the operation of the ship is limited or disabled as a result of a major engine failure, serious income loss occurs due to dwell time. The most prominent loss of the shipping company is the loss of rent income. As the repair period extends the economic loss of the shipping company gets bigger and bigger. Because time equals money for shipping companies in such a competitive market. Therefore, the most logical course of action is to handle repair activities in the operation area by having the repair done at the most available and nearest shipyard and acquiring the spare part from the nearest supplier. In case of failure that hampers the operation of the ship, the most crucial issue is to eliminate it as soon as possible. In this thesis, an integrated and systematic model is developed as a decision support tool to minimize dwell time for the repair activity based on condition monitoring system in case of major engine failure that the ship encounters at sea. In essence, the main objective of the model is to minimize repair dwell time. The study starts with a literature review and structured interviews carried out with experienced professionals in the shipping sector. To reach an optimal solution, a model is designed to handle the repair and spare part ordering processes jointly in the context of condition-based replacement with the help of Condition Based Monitoring (CBM) and Internet of Things (IoT) technologies. To achieve this an algorithm is developed and mathematically formulated. To simulate and verify the model a new software is developed by implementing this algorithm. Following the statistical analysis of the collected data, test input data is generated for input parameters for the test and verification of the model. Test runs are carried out with generated input data to evaluate the outputs of the model via developed simulation software. As a result of the test and verification process, it is confirmed that the model works as it is expected and the outputs and the results are reliable. Keywords: Maritime, shipping, repair, shipyard, spare part lead time, spare part ordering, Condition Based Monitoring (CBM), Internet of Things (IoT).