Use Cases

MLOps Pipeline for Autonomous Welding Robots

Our work with a US-based Autonomous Welding Robot help streamline ML models development by continuously re-train and evaluate ImageML as new images become available, continuously.

The Challenge

Our client goal is in maintaining the peak performance of their robotic welding accuracy. High quality data and timely Models training are crucial to the efficacy of the tasks executed by robots. The dynamic nature of their operations required constant adaptation to new data and scenarios, demanding a sophisticated approach to model management and training.

MLOps Pipeline
Data Preparation and Training

The idea of MLOps Pipeline is not new, but not everyone get it working end-to-end. Our team worked with client to develop a full end-to-end MLOps pipeline that continuously takes production data, transform and prepare features for Image model training

Evaluate and Deploy
Automate model evaluation and deployment

Our MLOps Solution help manages model versioning, evaluate model performance and accuracy. In some cases, improved models that meet certain accuracy threshold can be deployed to production automatically. This allows our client to achieve fully autonomous ML lifecycle


Robots that learn continuously

The welding robots look almost like they can learn on their own, day after day. Our clients is able to stay on top of ever changing manufacturing requirements.

Autonomous Welding Robots experienced a substantial increase in welding precision and efficiency. Downtime due to outdated models was minimized, leading to improved overall productivity. The MLOps implementation not only solved immediate challenges but also future-proofed their operations for evolving demands.