Why traditional automation falls short in automotive
The automotive industry demands flexibility, speed and precision.
Yet traditional automation struggles to keep up with evolving models, customization, and market pressure.
Here’s where the biggest pain points lie.
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1. Can’t handle part variety
Downtime and costly reprogramming results from predetermined robot paths not being able to handle part variety or process changes. This makes it harder to adapt to new models or parts.
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2. Can’t handle randomized parts
Robots without 3D vision struggle to pick parts from unstructured environments, such as randomly oriented parts in bins, on pallets, or stacked in layers - limiting real-world automotive manufacturing applications.
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3. Fixture dependency
Traditional automation in automotive manufacturing requires expensive fixtures to position car parts consistently.
This drives up costs and makes scaling or introducing new products more difficult.
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4. Labor-intensive tasks
Sealing, sanding, deburring, and assembly typically involve labor-intensive manual work.
These tasks are repetitive, ergonomically challenging, and error-prone, making it difficult to achieve consistent quality.
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5. High downtime & maintenance costs
Frequent stoppages during changeovers and manual intervention eat into productivity and profitability - especially as model lifecycles shorten.
Do you recognize these challenges?
Contact us today...
and stay tuned for the upcoming release of our free Automotive Expert Guide!
