Artificial Intelligence (AI) and Knowledge-Based Engineering (KBE) in Ship Design: Bridging Tradition and Technology Through ACQUAINT
Tufail Shahzad; Peng Wang; Peter van Lith; Jacques Hoffmans
💡 Our article explores the transformative impact and probes into the groundbreaking integration of Artificial Intelligence (AI) and Knowledge-Based Engineering (KBE) within shipbuilding.🌟🤖🧠💻
🔍Explore further into the capabilities of our innovative AI/KBE module, AQUAINT, designed specifically for bespoke shipbuilding. Discover how AI/KBE-driven solutions are reshaping shipbuilding processes, optimizing efficiency, and advancing precision in marine engineering. 🚢🌊
Introduction
In shipbuilding, the design and construction processes often involve repetitive tasks and the need for consistent structural elements across various vessels. This research paper presents the implementation of Template Oriented Modeling (TOM), an in-house developed CAD feature that offers an innovative solution to address these challenges. TOM introduces automation and efficiency by streamlining the ship design and construction processes. By utilizing predefined templates and dynamic parameters, TOM significantly reduces the need for manual repetition, resulting in time savings and increased productivity. This paper focuses on the issue of repetitive manual work in shipbuilding and highlights TOM as a transformative approach to overcome this challenge. The motivations, benefits, and innovations associated with TOM are thoroughly examined, emphasizing its potential to revolutionize the shipbuilding industry. We presented a fully functional example demonstrating the effectiveness of TOM in achieving streamlined workflows and improved design consistency.
Despite the limited use of artificial intelligence/knowledge-based engineering (AI/KBE) in industries with small series or one-off designs, our study demonstrates the technical feasibility and potential benefits of implementing AI/KBE in ship design processes. This research presents the development of “ACQUAINT,” uniquely designed to address the complexities inherent in bespoke shipbuilding. Central to this module is a robust AI-driven inference engine, integrated seamlessly with AutoCAD through a Python-based interface, facilitating a novel approach in shipbuilding’s detail and production design phases. The module’s capability to generate optimal designs autonomously—grounded in a deep understanding of design rules, constraints, and requirements—substantially reduces the reliance on human interaction. Our initial proof of concept with “ACQUAINT” showcases measurable advancements in ship design accuracy and efficiency, highlighting AI KBE’s transformative impact in shipbuilding and setting a foundation for future research and practical applications.
Acknowledgement
We would like to thank the Dutch government organization “SME Innovation Stimulation Region and Top Sectors (MIT)” for generously funding this research through the Netherlands Enterprise Agency (Rijksdienst voor Ondernemend Nederland: RVO) grant number “STIM-00061.” We also want to express our gratitude to our colleagues at the R&D department of MasterShip software for their invaluable feedback and support throughout the research process. Their contributions were essential to the achievement of our research goals.
Keywords
ship design; artificial intelligence; knowledge-based engineering; self-learning system; software development; ACQUAINT; CAD/CAM software; computers in construction; computers in design; modernization; ship structure
#AIinShipbuilding #ShipDesign #AI #KBE#MarineEngineering #PracticalShipDesign #mastership ‍‍‍‍‍‍‍‍‍#Innovation #BespokeShipbuilding #Shipbuilding #NavalArchitecture #AQUAINT #ShipbuildingInnovation #MaritimeTechnology #TechInShipbuilding #ProcessInnovation ‍‍‍‍‍#DigitalTransformation MasterShip SNAME ‍‍‍‍‍‍‍‍‍‍NPU INTERNATIONAL COLLEGE
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Jacques Hoffmans
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 jh@mastership.nlÂ
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