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Impact of hybrid workpieces on statistical process monitoring of machining operations

  • Berend Denkena
  • , Benjamin Bergmann
  • , Matthias Witt*
  • *Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer review

Abstract

This paper examines the influence of material transition on a process monitoring approach based on confidence limits for friction-welded EN-AW6082/20MnCr5 shafts. Process error sensitivity was investigated for different control and acceleration signals as well as for the first principal component during slot milling. To that end, three material defects were applied by a hole, stainless steel rod, and high-speed steel drill. The signal changes caused by these defects were characterized by amplitude, duration, and shape. Based on the information, errors were simulated for each signal, which were used to evaluate the confidence limits and to compare the detection time for the entire machining process. A new methodology was developed to evaluate process monitoring systems with regard to error sensitivity. It was determined that errors were not detected during the entire process due to the material transition. By combining features with the first principal component analysis, the sensitivity of process monitoring had been improved by more than 50%.

Original languageEnglish
Pages (from-to)765-771
Number of pages7
JournalInternational Journal of Advanced Manufacturing Technology
Volume99
Issue number1-4
E-pub ahead of print10 Aug 2018
DOIs
Publication statusPublished - Oct 2018

Keywords

  • Hybrid parts
  • Milling
  • Monitoring
  • Sensor data fusion

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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