Best-Fit Assembly Uses Stationary-Mounted Sensors

inos G-Guide automated assembly and robot guidance solutions have been engineered to support the most complex and demanding applications in automotive vehicle assembly. Multiple paint colors, challenging materials and substrates and ever-tightening tolerances all fall within the capability and expertise of the inos systems.

As a vehicle moves down the production line into an assembly cell, inos G-Sens sensors, mounted directly into the robot gripper, measures the closure panel (eg door, tail-gate, hood, windshield) before being picked-up. This robotic measurement eliminates the need for expensive, precision mechanical tooling and ensures that each closure panel is picked-up identically by the robot for every assembly cycle.

When the vehicle is in position, the robot moves the closure panel into a pre-deck position, immediately over the vehicle opening, where the closure panel is again measured to guarantee no motion slippage has occurred during the robot transfer process. The location and dimensions of the vehicle opening is also measured before assembly occurs.

The inos G-Guide system generates transformation offset coordinates for the robot to ensure optimal closure panel placement into the opening. If deemed desirable, multiple iterative loops of the measurement step can be performed to increase overall system performance. The panel is placed into the vehicle opening and attached with a final gap and flush quality check also being performed at the end of the cycle to validate and document the guided robot vehicle assembly success.

Due to the nature of the ‘closed system’, the robot gripper and sensors form a single unit, thus automatically compensating for any thermal variation or robot component wear.

Robotic best fit assembly using stationary mounted sensors offer the following benefits:

  • Shorter standoff sensors (minimize ambient environment effects)
  • Reduce mechanical fixturing costs
  • Automatic compensation for thermal variation and robot wear
  • Effectively allows for component picking

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