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As vehicle innovation continues to evolve rapidly, automotive lighting systems are becoming increasingly complex. From headlamps to taillamps and interior systems, signature lighting systems and designs are both a marquee aesthetic and critical functional systems in enabling autonomous driving.

 With advanced design comes increased manufacturing complexity and further electronics. This generally increases the costs of manufacturing the lighting components as well as warranty cost risk if a problem occurs once a vehicle is on the road. 

“From a manufacturing perspective, the pressure for flawless execution of new product launches with zero defects is more critical than ever,” explains James Finch, Director of Customer Success. “End-of-line visual inspection and off-line sample testing only offer a partial view, while advanced machine vision solutions can provide insights on every part.”


Overcoming issues means getting a quality assessment of every component earlier in the manufacturing process. During the plastic welding process, one of the challenges has been the inability to verify quality along the entire weld path without destructive testing. Eigen’s solution leverages thermal imaging to capture multiple views of the part during the weld and fuse them into a complete digital twin of the weld path. 

When image and process data are combined at the (edge device), machine learning models are leveraged to deliver real-time alerts to the shop floor team of any issues detected. These alerts can also be shared with the extended team via text message for quick mobile access and decision-making.


With real-time quality and process monitoring in place, the production and quality teams can leverage the software to focus on flagged parts and connect the dots between process variation and defects.   

“While our active monitoring prevents parts with inadequate welds from moving beyond the weld cell, we knew that our customers wanted to know more,” says Finch. “So we developed advanced analytics and insights features that provide the context teams need to quickly uncover the cause of defects and take steps to prevent them.”

At a time when resources are stretched, the solution becomes an extra set of eyes with consolidated data/part records and automated insights to help teams save time and focus on what matters.  

The benefits Eigen’s platform delivers on one cell or line are easily duplicated on other cells or extended to additional applications. It can be scaled to additional weld cells or connected to other upstream/downstream manufacturing processes to fully build out the digital part record.

“Consider the power of a deployment where we’re ingesting data from the injection molding machines and linking it to the inspection data at the weld cell,” says Finch. “Issues may not be tied to a single process, so broader analytics and insights open the door to full process optimization for maximum throughput with zero defects.”  

Additional processes, cells, and lines within or across factories are all accessible in Eigen’s online software. As more data sources are added, analytics and insights expand from one machine to multiple, enabling greater quality consistency and continuous improvement across operations.

Click here to learn how Eigen is helping a Tier 1 lighting manufacturer avoid quality and process issues.