Accelerate craftsmanship training with AI-powered learning
Join CraftPro_SBO and explore how AI-assisted training and adaptive feedback can help you transfer craftsmanship skills more efficiently, reduce dependence on expert trainers and accelerate workforce development.
Challenge
Manufacturing companies increasingly struggle to transfer essential craftsmanship skills to new employees. Activities such as welding, brazing, caulking and spray painting require practical expertise that is often difficult to document and teach. As experienced workers retire and skilled labour becomes harder to find, preserving and transferring this knowledge is becoming a growing challenge.
Today, craftsmanship training largely relies on experienced workers who demonstrate techniques, supervise trainees and provide feedback through repeated practice. Depending on the skill, reaching independent performance can require several months of intensive hands-on training. This approach is time-consuming, costly and difficult to scale.
Although technology-assisted training solutions can assess task execution and provide feedback, they often lack the flexibility to support trainees throughout their learning journey. Training programs still require substantial expert input and rarely adapt exercises, assessments and feedback to each trainee's evolving skill level.
Project Goals
With this project (CraftPro_SBO), we aim to develop an integrated, AI-supported framework for creating and delivering adaptive craftsmanship training programs, reducing the time, cost and expert effort needed to develop practical skills.
The project combines AI-assisted training program development, advanced skill modelling and personalised learning strategies. By extracting knowledge from documents, videos, sensor data and expert input, the framework will help structure training content while accounting for different execution styles, task outcomes and individual learning progress.
Adaptive training methods will automatically adjust exercises, learning sequences and feedback to each trainee's needs. The project will also investigate technologies such as haptic feedback and collaborative robots to provide more intuitive, hands-on guidance.
We target at least 50% less expert time to configure, deploy and deliver training programs, and a 20% reduction in time-to-competence, while maintaining or improving task quality.
By making craftsmanship training more scalable and personalised, we aim to help manufacturers and training providers preserve valuable expertise, accelerate employee development and reduce dependence on experienced trainers.
Join our research
We are looking for companies that want to participate in our research and work with us on the valorisation of the project.
Interested?
Then complete the form below.
