Ensure Quality of Battery Cells with the help of an AI Solution
duration | 2 hours
Description
The course will deliver a full boiler plate for ai-based quality assurance in battery welding. It starts with consideration of the laser-based welding process that joins cell connectors. Selection of suitable sensors and a discussion of data acquisition will follow before code is being created to analyse the data.
Learning Outcomes
By the end of this course, participants will be able to:
- Consider suitable sensors to monitor process properties in laser-based welding
- Plan the integration of such sensors into manufacturing equipment
- Prepare data storage to acquire actual data from the sensor system
- Set up a programming environment for the AI solution
- Implement a first set of algorithms for training and evaluation of acquired data
Introduction to laser-based welding
duration | 0.5 hours
Learning Outcomes
- Understand parameters of the laser-based welding process
- Identify quality indicators for cell welding
- Consider properties to monitor for determination of product quality
Activities
- Interactive lecture
- Group discussion: “How do deviations look like?”
- Case example of laser-based battery welding
Sensor selection and application
duration | 0.5 hours
Learning Outcomes
- Understand sensor properties
- Map sensors to process properties
- Select and apply sensors for specific process features
Activities
- Lecture on sensor properties
- Group exercise: Mapping of sensor capabilities to process features
- Quiz
Create an AI data processing pipeline
duration | 1 hours
Learning Outcomes
- Set up a software development environment
- Select promising AI algorithms
- Decide about pre-processing of acquired data
- Run model training on a split data set
- Validate the trained model on a test data set
Activities
- Excercise: installation and set up of programming environment
- Lecture with mapping of suitable algorithms
- Excercise: execute training and validation