MONITORING INCREASING PIECING FAULTS

MILLMASTER “LAB TREND”

With its “Lab Trend”, MillMaster TOP offers a comprehensive analysis tool for determining fluctuating yarn properties and their causes. Deviations in the yarn quality produced may result from the following factors:

  • Raw material change
  • Settings changes
  • Wear and tear
  • Dirt
  • Climate change

This example shows spinning mills can use the “Lab Trend” to know how many piecing events have taken place on the ring spinning machine and whether there were any fluctuations.

The chart (fig. 1) shows a massive faults increase in the yarn classes B2, C2 and B3.

Figure 1

A high number of such defects in these classes will lead to interruptions in the subsequent processes and adversely affect the fabric appearance. It is therefore vital to immediately find out the reasons for the emergence of these yarn faults.

 

Solutions & benefits

The tracing of the trigger is very important in enabling appropriate countermeasures to be initiated - and, with the Loepfe yarn classification table, this is a simple task.

The online yarn classification table shows what might have caused an increased number of faults in the classes B2, C2 and B3:

B2

  • high RF speed
  • loose or spun in fly
  • settings of spacers
  • piecing faults
  • damaged aprons

C2

  • high RF speed

  • spacers settings

  • drafting faults

  • piecing faults

  • damaged aprons

  • excessive trash

B3

  • high RF speed

  • loose or spun in fly

  • piecing faults

  • unsuitable travellers

This list shows that the reason for the strong increase is probably due to a massively increased number of piecing faults on the ring-spinning machine.

The clear presentation of quality changes by the "Lab Trend" gives the spinner the ability to keep track of changes in the process at all times. Extremely valuable and automated data evaluation allows immediate intervention in the event of disruptive incidents which would have a negative impact on efficiency or quality

Recommendation

Real-time data monitoring for winding

  • Production planning
  • Trend analysis
  • Mobility
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