A prediction tool for maintenance costs estimation during the design process of a ship engine room

Abstract When dealing with maintenance in ships engine room, the space available around machinery and systems (clearance) plays an important role may significantly affect cost of intervention. In a first part current research study Gualeni et al. (Ship Technol Res, 10.1080/09377255.2021.2020949, 2022), quantitative relation between costs increment due to clearance reduction is determined, using Bayesian approach General Linear Model (GLM), reference single item/component larger system Sánchez-Herguedas (Reliability Eng Syst Saf 207: 107394, 2021). This paper represents second activity it enforces systemic view over whole or Sanders Klein (Proc Comput Sci 8:413–419, 2012). The aim identify not only reduction, but also how reductions components/items interact system/machinery accessibility maintainability, meant as relevant emerging properties. properties are investigated through design application Hidden Markov Salvatier (Peer J 2: e55, 2016); i.e., modeled by process unobservable states. sequence states maintainability (which incorporates each one components) while evidence increase related reduction. By predicting states, therefore possible predict interactions components clearances determine property affected room design.