Machine learning based cycle time tracking and reporting for vehicles

A method, comprising:

• receiving, by one or more processors coupled with memory, from one or more cameras, a video stream that captures a component for a vehicle, the component disposed in a predetermined area;
• determining, by the one or more processors via one or more models trained with machine learning and based on the video stream, a type of the component;
• detecting, by the one or more processors, responsive to the type of the component matching a predetermined type and an analysis of a plurality of frames of the video stream with the one or more models, a welding arc and a duration the component is disposed in the predetermined area subsequent to detection of the welding arc;
• and
• performing, by the one or more processors based on the duration, an action to control a welding process for the component of the vehicle.

A vehicle manufacturing system, comprising:

• markings surrounding a welding area in a manufacturing facility;
• a camera oriented to capture image data from the welding area;
• and
• one or more processors, coupled with memory, to:
• receive, from the camera, a video stream that captures a component for a vehicle, the component disposed in the welding area;
• determine, via one or more models trained with machine learning and based on the video stream, a type of the component;
• detect, responsive to the type of the component matching a predetermined type and an analysis of a plurality of frames of the video stream with the one or more models, a welding arc and a duration the component is disposed in the predetermined area subsequent to detection of the welding arc;
• and
• perform, based on the duration, an action to control a welding process for the component of the vehicle.