AI Discussion and Progression: More than 1,000 individuals attend real-time debates on the application of AI in engineering fields
In a groundbreaking move, the CADFEM Blueprint Live Talk for Engineers was directed at an international audience for the first time, attracting over 1,000 participants from around the world. The live talk featured Ana Luiza Pinto Queiroz, head of process development at the Irish biotech company APC, and Kevin Cremanns, co-founder and chief research & development officer of the AI startup PI Probaligence. The duo shared their experiences from a joint project where they began using AI in APC's product development two years ago.
The topic of the live talk was "How engineers successfully implement AI projects". The discussion focused on the introduction process, including the first steps, proof of concepts, unexpected challenges, and the current status of the project. Engineers gained many insights and concrete answers to common questions from the focus on a real AI project.
Progress Over the Past Two Years
The project started with a detailed assessment of APC’s existing product development workflows to identify areas where AI could add the most value. Ana Luiza contributed deep domain knowledge of APC’s products and engineering requirements, while Kevin developed customized AI models tailored to those needs.
Collaborative efforts led to the creation of AI tools focused on predictive analytics for product performance and automated design optimization. The AI models were integrated into APC’s product lifecycle management (PLM) systems, allowing for real-time data analysis and decision-making support. Extensive testing cycles were conducted to fine-tune AI models based on feedback from product teams, helping reduce design iteration times and improve accuracy in predicting product failures.
APC reported increased efficiency in their development process, with notable reductions in time-to-market and prototyping costs. The collaboration set a new standard within APC for using AI as a complementary tool in engineering and product design.
Key Success Factors
The success of the project can be attributed to several key factors. Strong cross-functional collaboration between Ana Luiza's deep engineering expertise and Kevin's AI proficiency created a complementary partnership that ensured AI solutions were practical and aligned with real engineering challenges.
Clear alignment on goals kept the project focused and outcome-driven. Both teams had a shared vision to enhance APC’s product development efficiency. An iterative development approach enabled continuous model improvement, ensuring the AI tools met the evolving needs of the product teams.
Integration with existing systems facilitated smooth adoption by product engineers and decision-makers. Embedding AI capabilities directly into APC’s workflows and PLM system was crucial for this smooth adoption. Data availability and quality played a critical role, with APC’s commitment to data management ensuring the success of the AI project.
Despite the progress made, over 50 percent of the companies have not yet started with AI or are still at the very beginning. The live talk served as an inspiring example of how AI can revolutionise product development processes, offering valuable insights for engineers and companies embarking on their AI journey.
The adoption of AI in the product development process at APC has been facilitated by the integration of AI models into their PLM systems, allowing for real-time data analysis and decision-making support.
The successful implementation of AI in engineering projects relies on factors such as strong cross-functional collaboration, clear alignment on goals, and smooth integration with existing systems.
