A Governance-Aware Methodological Framework for Cognitive AI Integration in Marine CAD: A Conceptual Pipe Routing Use Case

This paper proposes a governance-aware methodological framework for the integration of Cognitive Artificial Intelligence into marine CAD environments. Unlike existing approaches that focus on isolated optimization or prediction tasks, the proposed framework introduces a structured architecture combining engineering knowledge corpora, hybrid AI reasoning, and CAD-based interaction within a traceable and regulatory-aware workflow. The contribution of this work is methodological rather than domain-exhaustive. The framework is illustrated through a conceptual pipe routing use case, selected as a representative high-constraint design subsystem involving spatial reasoning, compliance verification, and iterative coordination. A normalized performance evaluation model is defined to estimate improvements in design efficiency, convergence, compliance validation and rework reduction. Although the validation is conceptual, the results are consistent with reported improvements in AI-assisted engineering workflows. The proposed framework gives a basis for integrating AI into marine CAD environments, aligned with newer digital ship design and Shipyard 4.0 approaches.

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Publication Details

Journal
Journal of Marine Science and Engineering
Published
2026-07-23
DOI
https://doi.org/10.3390/jmse14151352
Primary Topic
Manufacturing Process and Optimization
Type
article
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article

A Governance-Aware Methodological Framework for Cognitive AI Integration in Marine CAD: A Conceptual Pipe Routing Use Case

Rodrigo Pérez Fernández, Diego Fernández Casado
Journal of Marine Science and Engineering
Manufacturing Process and Optimization
article

A Governance-Aware Methodological Framework for Cognitive AI Integration in Marine CAD: A Conceptual Pipe Routing Use Case

Rodrigo Pérez Fernández, Diego Fernández Casado
article en

Abstract

This paper proposes a governance-aware methodological framework for the integration of Cognitive Artificial Intelligence into marine CAD environments. Unlike existing approaches that focus on isolated optimization or prediction tasks, the proposed framework introduces a structured architecture combining engineering knowledge corpora, hybrid AI reasoning, and CAD-based interaction within a traceable and regulatory-aware workflow. The contribution of this work is methodological rather than domain-exhaustive. The framework is illustrated through a conceptual pipe routing use case, selected as a representative high-constraint design subsystem involving spatial reasoning, compliance verification, and iterative coordination. A normalized performance evaluation model is defined to estimate improvements in design efficiency, convergence, compliance validation and rework reduction. Although the validation is conceptual, the results are consistent with reported improvements in AI-assisted engineering workflows. The proposed framework gives a basis for integrating AI into marine CAD environments, aligned with newer digital ship design and Shipyard 4.0 approaches.

Journal of Marine Science and EngineeringVol. 14(15)
Siemens (Spain) (ES), Universidad Politécnica de Madrid (ES)
Life below water
Openalex Percentile: Top 9%
Manufacturing Process and Optimization
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A Governance-Aware Methodological Framework for Cognitive AI Integration in Marine CAD: A Conceptual Pipe Routing Use Case — Rodrigo Pérez Fernández, Diego Fernández Casado · Journal of Marine Science and Engineering (2026) | TGRS Research Map | TGRS