Modelling Maintenance
Cost Optimised Maintenance in Shipping
S.R.A. Moussault (TU Delft - Mechanical Engineering)
J.F.J. Pruyn – Mentor (TU Delft - Ship Design, Production and Operations)
Geert van IJserloo – Mentor (Anthony Veder)
A. Kana – Graduation committee member (TU Delft - Ship Design, Production and Operations)
Y. Pang – Graduation committee member (TU Delft - Transport Engineering and Logistics)
Bruno Lopes dos Santos – Graduation committee member (TU Delft - Air Transport & Operations)
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Abstract
The current operational cost estimate applied by shipping management companies is insufficiently valid and accurate for determining the operational budget. Most shipping management companies include scheduled maintenance jobs in the operational cost calculation. Scheduled maintenance does not take unforeseen maintenance into account. In retrospect, unforeseen maintenance makes up approximately 8\% of the total operational costs. The estimation of the operational costs can be improved by including the unforeseen maintenance costs. Improved operational cost calculations lead to better substantiated maintenance policy decision-making. Therefore, the (unforeseen) maintenance costs over the lifetime of a vessel are modelled. This research focuses on maintenance cost calculations, based on failure behaviour. First, it is explained how the Maintenance Cost Model calculates and compares the costs of different maintenance policies. Thereafter, the model is validated in a case study. The achieved cost reductions resulting from the case study varied from 0\% to 70\%, with a conservative average of 16\%. Next, the case study conclusions are assessed in a sensitivity analysis. The model generates a, system specific, cost based ranking of the maintenance policies. The ranking can be used by shipping management companies, to obtain a better substantiated system specific maintenance policy. The developed model in this research is generally applicable and proves the concept. The research concludes with recommendations for future research, which includes further expansion of the Maintenance Cost Model and the possibilities to increase the likelihood of the number of replacements.