Automated RAM Installation

Shows a robot picking a RAM module, aligning it above the motherboard slot, and pressing it into place with controlled force.

The sequence highlights server assembly automation where visual servoing and insertion feedback protect delicate connectors while improving repeatability.

Flexiv

Flexiv

Adaptive Robotics

Use case

ram installation

Category

Electronics Assembly And Testing

Key capability

visual servoing, force control

Storyboard

What the video shows

The storyboard shows a robot picking a RAM module, aligning it above the motherboard slot, and pressing it into place with controlled force.

  1. Step 1

    Prepare the workcell, fixture, part, or target surface shown in the storyboard frames.

  2. Step 2

    Locate and align the robot or tool for ram installation.

  3. Step 3

    Execute the task with visual servoing and monitored robot motion.

  4. Step 4

    Confirm the placement, contact path, inspection result, or finished surface before repeating the cycle.

Challenge

Why this task is difficult

Automated RAM Installation requires repeatable execution in electronics assembly and testing, where alignment, controlled contact, and process consistency can be difficult to maintain manually.

Value

Operational value

The sequence highlights server assembly automation where visual servoing and insertion feedback protect delicate connectors while improving repeatability.

Deployment layer

How Robita AI helps

Robita AI turns this kind of Flexiv demonstration into a deployment plan: we assess the manual workflow, define the tooling and fixture assumptions, validate the robot capability, and map the pilot path from first test to production rollout. For electronics assembly and testing applications, that means connecting the visible robot motion to practical questions like cycle time, safety, operator handoff, data capture, and integration with the existing workstation.

Complexity reduction

How Flexiv force control reduces complexity

Flexiv force control lets the robot adapt during contact instead of relying only on exact position commands. That reduces the need for heavy custom mechanics, perfectly rigid fixtures, and long exception programming because the robot can feel insertion, pressure, and surface contact while it works.