Accessibility for maintenance in engine room: a prediction tool for operational costs estimation during the design process

Abstract

When dealing with maintenance in ships engine room, the space available around machinery and systems (clearance) plays an important role and may significantly affect the cost of the maintenance intervention. In a first part of a current research study (Gualeni et al., 2021), a quantitative relation between the maintenance costs increment due to the clearance reduction is determined, using a Bayesian approach to General Linear Model (GLM), with reference to a single item/component of a larger system (Sánchez-Herguedas, 2021). This paper represents the second part of the activity and it enforces a systemic view over the whole machinery or system (Sanders et al., 2012). The aim is to identify not only the relation between maintenance costs and clearance reduction, but how the clearance reductions of the single components/items interact and affect the whole system/machinery accessibility and maintainability, meant as relevant emerging properties. The system emerging properties are investigated through the design and application of a Hidden Markov Model (Salvatier et al., 2016); i.e., the system is modelled by a Markov process with unobservable states. The sequence of states is the maintainability of the system (which incorporates each one of the single components) while the evidence is the increase in cost of maintenance related to the space reduction. By predicting a sequence of states, it is therefore possible to predict the interactions between the system components clearances and determine how the emerging maintainability property is affected by the engine room design.