Acoustic Emission Based In-process Monitoring in Robot Assisted Polishing

Lukas Pilny, Giuliano Bissacco, Leonardo De Chiffre, J. Ramsing

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Abstract

The applicability of acoustic emission (AE) measurements for in-process monitoring in the Robot Assisted Polishing (RAP) process was investigated. Surface roughness measurements require interruption of the process, proper surface cleaning and measurements that sometimes necessitate removal of the part from the machine tool. In this study, development of surface roughness during polishing rotational symmetric surfaces by the RAP process was inferred from AE measurements. An AE sensor was placed on a polishing tool, and a cylindrical rod of Vanadis 4E steel having an initial turned surface roughness Ra = 3.1 μm was polished using a silicon carbide stone of grit size 600 in 40 polishing passes down to Ra = 0.07 μm. The polishing task was performed in five steps and after 4, 8, 20, 30, and 40 passes the resulting surface roughness was measured. The results show that with proper AE signal processing, the development of surface roughness in the RAP process can be monitored by AE measurement. The AE based monitoring allows in-process determination of the right moment for changing a polishing tool when applying a given set of parameters is no longer effective to create smoother surface, thus improving the efficiency of the process. It also allows for intelligent process control and generally enhances the robustness and reliability of the automated RAP system in industrial applications.
Original languageEnglish
Publication date2013
Number of pages6
Publication statusPublished - 2013
Event 11th International Symposium on Measurement Technology and Intelligent Instruments - Aachen, Germany
Duration: 1 Jul 20135 Jul 2013
Conference number: 11

Conference

Conference 11th International Symposium on Measurement Technology and Intelligent Instruments
Number11
CountryGermany
CityAachen
Period01/07/201305/07/2013

Keywords

  • Robot assisted polishing
  • Acoustic emission
  • In-process monitoring
  • Surface roughness

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