How C-Job and Amogy retrofitted a tugboat for zero-carbon power | Data-driven Shipbuilding

How C-Job and Amogy retrofitted a tugboat for zero-carbon power | Data-driven Shipbuilding

In this podcast episode, we talk with Niels de Vries from C-Job Naval Architects and Abigail Jablansky, Head of Projects at Amogy, about how they retrofitted a tugboat to run on ammonia, taking it all the way from concept design to commissioning on a public waterway. They share how a first-of-a-kind technology, tight space constraints, and a parallel development process shaped every decision, and how Cadmatic kept engineering teams aligned throughout.   Key topics in this episode: * How Amogy's ammonia-to-power system works and why ammonia is a promising zero-carbon fuel for maritime applications. * What made this retrofit different: new technology, no prescriptive rules, and a product still in development during design. * How 3D scanning at multiple project stages defined the design basis and unlocked space for integration. * How the 3D model kept C-Job, Amogy, the shipyard, and remote engineers coordinated throughout the project. * Key lessons from delivering a first-of-a-kind project, and what comes next for Amogy.

Building smarter shipyards: aligning data, people, and value | Data-driven Shipbuilding

In this podcast episode, we talk with Evgenii Egorov, PLM Project Manager, and Miia Martinsuo, Professor at Turku University, about how shipyards can bring people, data, and processes in sync across the full lifecycle. They share how aligning value between stakeholders, improving knowledge flow, and building the right skills base supports more predictable and connected projects. Key topics in this episode: * How different stakeholders define value and why alignment matters. * Mapping shipbuilding activities across the full lifecycle to spot improvement areas * Building a knowledge management system to connect scattered information. * The role of AI in helping teams find and use the right data faster. * Developing skills to support digital tools and human-centric shipbuilding. SEUS/MOOC: Data-Driven Shipbuilding open online course can be accessed via https://digicampus.fi [https://digicampus.fi/]. Register using a Google account, enrolment key SEUS-Learning.

From scan to sea trials: modernizing an engine room | Data-driven Shipbuilding

In this podcast episode, we talk with Ștefan Carpov and Alexandru Pazargic from GLO Marine about how a full engine room modernization project was delivered from 3D scanning to sea trials. They share how a clean-slate approach, combined with accurate data and strong coordination, supports complex retrofit work on aging vessels.   Key topics in this episode: * How 3D scanning before and after stripping supports accurate design decisions * Designing a fully modernized engine room, not just replacing equipment * Using CADMATIC for 3D modeling, point cloud handling, and production drawings * Coordinating multiple disciplines using shared data and clear documentation * Managing installation challenges in tight spaces and retrofit conditions

Strong administration, faster ship design | Data-driven Shipbuilding

In this podcast episode, we talk with Przemysław Górski at Górski CAD Solutions about why software administration has a direct impact on how fast and reliably you can deliver ship design. With more than 15 years of experience supporting shipyards and design offices across Europe, he shares what a well-configured Cadmatic environment looks like and what it changes for everyday work.   Key topics in this episode: * How setup, libraries, templates, and rules help designers work faster * How better configuration improves drawing quality and reduces errors * Keeping 3D models and documentation in sync from design to production * Using automation to support consistency across teams and suppliers * Preventing issues that usually show up late during production or installation

Value of data: How smarter models empower engineering | Data-driven Engineering

Industrial companies are sitting on a goldmine of data - but much of it is locked away in PDFs, legacy drawings, and unstructured documents. What if that data could be transformed into intelligent, connected information that fuels digital twins, simulation, and AI?   In this episode of the Data-driven Engineering, we dive into the challenge of turning decades of legacy engineering material into structured, semantic data that both humans and systems can truly understand.   Mikko Yllikäinen (VP, Product Creation at Cadmatic) is joined by Antti Villberg from Semantum to discuss: * Why so much valuable engineering data gets “lost” in document handovers * The role of semantic data models and knowledge graphs in making information machine-readable * How legacy P&IDs, PDFs, and even laser scans can be converted into intelligent models * Real-world examples * How standards like ISO 15926 and OPC UA enable interoperability and plug-and-play integration * Why structured data is the foundation for successful AI in industrial environments   The key takeaway? Data alone isn’t enough. When data becomes meaningful, connected, and standardized, it unlocks innovation, smarter collaboration, and entirely new possibilities for the future of engineering.