## 3 Materials and Methods
Three-dimensional modelling has been successfully employed to represent and analyse complex systems such as offshore installations [79]. Moreover, integrating data from different sources, such as inspection, condition history, engineering characteristics, and simulations, was essential to gain comprehensive insights into the equipment's conditions [80]. External corrosion data were collected through systematic inspections, and the integrated analysis and decision-support environment was applied to generate optimised maintenance plans based on risk assessment criteria. Demonstration in real offshore contexts validated the artefact's efficacy and applicability in industrial settings [81]. The artefact was evaluated on the basis of the results obtained in the case studies. Performance indicators such as resource allocation efficiency, the effectiveness of damage reduction, improvements in regulatory compliance, and coverage of critical systems were analysed. Feedback from offshore maintenance experts was also collected to refine the \begin{table}
\begin{tabular}{c l l} \hline \hline \# & **Module** & **Description** \\ \hline
1 & \
\begin{tabular}{l} \end{tabular} &
\begin{tabular}{l} This module sets the initial parameters of the maintenance \\ project, laying the foundation for effective planning. \\ \end{tabular} \\ \hline
2 & \
\begin{tabular}{l} Degradation progress prediction \\ \end{tabular} &
\begin{tabular}{l} This module employs machine learning models, specifically the \\ Random Forest algorithm, to predict corrosion progression \\ based on environmental and operational factors. \\ \end{tabular} \\ \hline
3 & \
\begin{tabular}{l} Exploratory analysis of the current situation \\ \end{tabular} &
\begin{tabular}{l} Provides a detailed view of the platform’s pre-maintenance \\ condition, using KPIs and graphical visualisations to facilitate \\ understanding of the current situation and the projected \\ scenario if no maintenance actions are taken. \\ \end{tabular} \\ \hline
4 & \
\begin{tabular}{l} Objective definition (strategies) \\ \end{tabular} &
\begin{tabular}{l} Allows for the selection of various optimisation strategies, each \\ focused on different critical aspects of maintenance: \\ \end{tabular} \\ \hline
5 & \
\begin{tabular}{l} Maintenance plan generation and 2D graphic analysis \\ \end{tabular} &
\begin{tabular}{l} Produces optimised plans and provides visualisations to \\ facilitate understanding and decision-making. \\ \end{tabular} \\ \hline
6 & \
\begin{tabular}{l} 3D visualisation of the maintenance plan \\ \end{tabular} &
\begin{tabular}{l} Integrates the results with 3D CAD/CAE models for a more \\ comprehensive spatial representation. \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Modules and descriptions of the APM prototype. artefact. Rigorous evaluation is crucial to verify whether the artefact met the proposed objectives and generated value for stakeholders [82]. The projects' results are communicated through scientific publications, conference presentations, and offshore industry workshops. This allows for the dissemination of the generated knowledge and the obtaining of additional feedback to improve the developed artefact. Effective communication is essential to promote the adoption and continuous evolution of the artefact [23].