Type of course:
Digital learning, Lesson
Language:
EN
Duration:
9 minutes
Workload:
2 hours
Proficiency:
Advanced
Target:
Professionals, Students
This nugget is developed by the University of Porto. It is about explainable defect detection and recipe recommendation for laser seam welding. This nugget has the same production example as nugget 6; again laser seam welding. The learning goals are to gain additional insights from the predictions produced by a model, understand its recommendations and leverage this knowledge by finetuning and perfecting the real time productions. Explainable AI (XAI) is introduced. For laser seam welding, the main process conditions are the metal sheet thicknesses. The goal is to find a set of parameters that influence the quality of the welding. The parameters used are input for a parameter explainable model. The analysis of the parameters of the laser welding show that width and depth are directly proportional and highly correlated. The parameter optimization process is done by the Basin-Hopping algorithm.
Learning outcomes
- Gain additional insights from the predictions produced by a model
- Identify recommendations produced by a model
- Leverage the knowledge by finetuning and perfecting the real time productions
Course Content
Topics
Digital Transformation, Artificial Intelligence (AI)