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Torque curves tell the whole story

2 minute(s) to read

Atlas Copco’s unique ToolsNet8 software can identify slight differences between completed fastenings and reference traces and return value to manufacturers.

‘The rundown’

The transition from pneumatic to electric tools brought manufacturing to the next level by:

  • improving quality
  • allowing more control
  • and expanding statistical capability

This transition also gave us the ability to capture a high frequency of data points throughout the tightening process also called ‘the rundown.’ 

These data points are plotted on an XY axis, based on torque-angle or torque-time. A good process is repeatable and every fastenings’ torque/angle signature should look nearly identical to the ones before and after it. Slight deviations would indicate potential manufacturing defects that a torque controller may not recognize, depending on the tightening strategies used within that application.

A torque controller’s job is to control and measure the tightening process performed by a tool. The torque controller is where one would configure an application’s upper and lower control limits, which then designate a fastening’s passing or failing rating by these parameters. 

False OK fastenings

Deviations from an expected torque trace can identify false OK fastenings. One type of false OK would be a tightening that falls in between the torque-angle lower and upper control limits, but also may present defect scenarios. 

Other issues such as cross-threading, bad seating, bolts stretching past elasticity – and even instances where a socket begins to wear – could all potentially pass as ‘good’ on a torque controller while harming build quality greatly.

Enter ToolsNet8

This is where Atlas Copco’s ToolsNet 8 software shines. The ToolsNet 8 software can identify when even the slightest changes occur by comparing a reference trace to fastenings performed by that same parameter set.

ToolsNet 8 can then push notifications to the right team member; enabling them to act quickly before the product ever leaves the plant. This feature has returned value to many manufacturers by proactively recognizing potential defect scenarios before they can impact the brand’s reputation. 

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