# The Multistate Reliability Assessment of Ship Hull Girders
## 1 Introduction
Under the influence of these influential factors, various structural defects develop in the forms of corrosion, crack, deformation, coating breakdown, and biofouling [11]. Different forms of corrosion occur in different ship hull areas and at different times of vessel operation. We can distinguish general corrosion and several other types of corrosion, like pitting, intergranular, galvanic, stress corrosion, corrosion fatigue, fretting, microbiological, crevice, erosion, and cavitation [12]. Various methods are used to inspect ships and detect defects that occur during the ship's life cycle. In this sense, the most important is visual inspection, which is carried out in the traditional way by an inspector at precisely defined time intervals, in accordance with the rules of the classification societies. In addition to the traditional methods of visual inspection, today, significant progress is achieved through the application of autonomous or semi-autonomous robots with missions inside and outside the ship's areas. Recently, unmanned vehicles and robots without a pilot onboard have been extensively used for underwater inspection [11; 13]. Furthermore, in addition to pressure, vacuum, roentgen, and magnet tests, various non-destructive inspection methods such as acoustic-based, electromagnetic, and image-based testing are used [11]. Robots are used as an alternative to monitoring the ship's hull in critical ship areas (closed spaces, high altitudes, etc.) in the traditional manner, although the majority of inspections are carried out traditionally even today. Through previous research on ships in operation, and the pursuit of safe and secure vessels, different condition assessment methods have been applied: formal safety assessment, time-variant reliability formulation, failure probability and reliability, inspection and maintenance planning, reliability-centered maintenance, etc. [5]. Recently, [PERSON] et al. proposed a dynamic multi-attribute decision-making method for risk-based ship design [14]. In recent years, automation, digitalization, and decarburization processes have contributed significantly to improving maritime safety. The digitalization of the world is booming, and the evolution of cloud computing, Internet of Things (IoT), Big Data analytics, Virtual Reality (VR), Augmented Reality (AR), Artificial Intelligence (AI), Machine Learning, Deep Learning, Neural Networks, etc., significantly improves maritime security [15]. Additionally, different types of sensors and measurement systems have been developed in marine engineering applications for structural health monitoring and in situ measurements of salinity, vibration, temperature, pressure, etc. [16]. So far, numerous studies have calculated corrosion rates over time in order to assess the degree of corrosion of individual structural areas of bulk carriers and tankers, probability of damage to particular structural areas, type of failure, and the influence of environmental factors and different corrosion classes. In addition, linear and nonlinear models have been well developed for transverse bulkheads and inner bottom plating [17; 18], for all structural elements and areas [19; 20]. Previous studies on the structural elements of fuel tanks and surrounding areas (sea water, ballast water, cargo, dry space) in bulk carriers in operation have considered corrosion damage in millimeters [17; 21] and the percentage of corrosion damage to structural plates [18], resulting in linear and nonlinear models of corrosion development. The reliability of fuel tanks and individual structural elements was the subject of paper [22]. Based on previous research, this study investigated the possibility of applying a multistate approach to reliability analysis on longitudinal girder plating. This paper is divided into five sections. The Section 2 presents the relevant database of measurement results from different ships and surveys. The Section 3 expounds on the theoretical aspect of the multistate approach for analyzing and improving steel plates' reliability.