Crankshaft Surface Processing

Shows crankshaft surface processing in a manufacturing cell, with the robot presenting a finishing tool to cylindrical metal features and process screens.

The workflow targets metal finishing where access angles, contact force, and repeatable tool paths determine surface quality.

Flexiv

Flexiv

Adaptive Robotics

Use case

surface processing

Category

Surface Finishing And Material Removal

Key capability

force control

Storyboard

What the video shows

The storyboard shows crankshaft surface processing in a manufacturing cell, with the robot presenting a finishing tool to cylindrical metal features and process screens.

  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 surface processing.

  3. Step 3

    Execute the task with force control 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

Crankshaft Surface Processing requires repeatable execution in surface finishing and material removal, where alignment, controlled contact, and process consistency can be difficult to maintain manually.

Value

Operational value

The workflow targets metal finishing where access angles, contact force, and repeatable tool paths determine surface quality.

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 surface finishing and material removal 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.