You will gain hands-on experience at the intersection of industrial automation, artificial intelligence, and manufacturing processes. A key focus of your internship will be supporting the implementation of AI-enabled industrial vision systems for the automatic monitoring of assembly and kitting processes, contributing to the development and training of image recognition models in a real manufacturing environment.
What you will do & learn
- Manufacturing Process Analysis: Analyze assembly and kitting processes to identify critical features to be monitored and the main potential sources of errors.
- Industrial Vision Systems: Support the development and implementation of industrial vision solutions aimed at automatically verifying the correct composition of kits and the execution of assembly operations.
- AI & Image Recognition: Contribute to the definition, training, and validation of image recognition models for component counting and anomaly detection.
- Data Analysis & Performance Monitoring: Analyze results and monitor key performance indicators related to quality, efficiency, and scrap reduction, supporting the evaluation of the implemented solutions.
- Technical Documentation & Standardization:
Support the preparation of technical documentation and the definition of operational standards required for the industrialization of the solution.
Assigned Project
You will contribute to a project focused on the implementation and industrialization of an AI-enabled vision system for assembly and kitting process control.
In particular, you will:
- Analyze current assembly and kitting processes and identify the critical features and potential errors to be detected;
- Support the development and configuration of an industrial vision system for automated process monitoring;
- Contribute to the collection and preparation of image data for AI model training and validation;
- Support the training and validation of image recognition models for component counting and anomaly detection;
- Evaluate the performance of the developed solution through dedicated quality and process KPIs;
- Collaborate with Production, Quality, and Manufacturing Engineering to integrate the solution into existing processes;
- Contribute to the definition of technical documentation and operating standards to support the industrialization of the solution.
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