Project Goals


  • Human-centric assembly monitoring system
  • Assembly step time and cycle time determination using vision cameras
  • Assembly operation's anomaly detection


  • Designing novel deep learning architectures
  • Identifying non-value-added activities without explicit training
  • Improving the current inference architecture


  • Integrating user feedback for model updates
  • Knowledge transfer of NVA activities
  • Development of a full-fledged assembly guidance system for AI in factories

Why do we do it?

In industries, up to 40% of the cost and 70% of the production time falls under assembly operations, either in intermediate assembly operations or in final finished product assemblies. Hence, the end-product quality and the lead time of a product are hugely impacted by the quality of the assembly operations

Current Challenges:

Hence, we propose a non-contact approach of monitoring the assembly operations using sensors like vision etc.

More details

Research Progress

We have developed an assembly monitoring system that can ac the following:

Interactive Application for SMIRL