Sensors for in-process and on-machine monitoring of machining operations

Alborz Shokrani, Hakan Dogan, David Burian, Tobechukwu D. Nwabueze, Petr Kolar, Zhirong Liao, Ahmad Sadek, Roberto Teti, Peng Wang, Radu Pavel, Tony Schmitz

Research output: Contribution to journalArticlepeer-review

4 Citations (SciVal)

Abstract

Machining is extensively used for producing functional parts in various industries such as aerospace, automotive, energy, etc. There is a growing demand for improved part quality and performance at lower costs from increasingly difficult-to-machine materials. Whilst modern machine tools are equipped with sensors for closed loop control of their axes’ movements and position, they provide minimal information regarding the cutting performance and tool condition. The integration of additional sensors into cutting tools, machine tools and/or their components can provide an insight into the machining performance. It also provides an opportunity to improve the machining process and reduce the need for post-process inspection and rework. This paper presents a comprehensive analysis of various sensors utilised for in-process and on-machine measurement and monitoring of machining performance parameters such as cutting forces, vibrations, tool wear, surface integrity, etc. Data transfer and communication methods, as well as power supply options for sensor-integrated systems are also investigated. Sensor integrated machining systems can potentially improve machining performance and part quality by early detection of errors and damages, maximising tool usage and preventing machining and tool wear induced damages. A combination of sensor data collection and intelligent sensor signal processing can further increase the capabilities of sensor integrated systems from process monitoring to active process control.
Original languageEnglish
Pages (from-to)263-292
Number of pages30
JournalCIRP Journal of Manufacturing Science and Technology
Volume51
Early online date17 May 2024
DOIs
Publication statusPublished - 31 Jul 2024

Funding

The authors would like to thank Prof. I. S. Jawahir form University of Kentucky who initiated and led the CIRP collaborative working group (CWG) on integrated machining performance for assessment of cutting tools (IMPACT). Petr Kolar and David Burian acknowledge the support of the Czech Ministry of Education, Youth and Sports under project number CZ.02.1.01/0.0/0.0/16_026/0008404, \u201CMachine Tools and Precision Engineering\u201D, financed by the OP RDE (ERDF). Alborz Shokrani, Zhirong Liao and Hakan Dogan acknowledge the support of the UK Engineering and Physical Sciences Research Council (EPSRC) under the grant number EP/V055011/1 for SENSYCUT project. The authors would like to thank Prof. Ibrahim S. Jawahir form University of Kentucky who initiated and led the CIRP collaborative working group (CWG) on integrated machining performance for assessment of cutting tools (IMPACT). Petr Kolar and David Burian acknowledge the support of the Czech Ministry of Education, Youth and Sports under project number CZ.02.1.01/0.0/0.0/16_026/0008404, \u201CMachine Tools and Precision Engineering\u201D, financed by the OP RDE (ERDF). Alborz Shokrani, Zhirong Liao and Hakan Dogan acknowledge the support of the UK Engineering and Physical Sciences Research Council (EPSRC) under the grant number EP/V055011/1 for SENSYCUT project.

FundersFunder number
European Regional Development Fund
Ministerstvo Školství, Mládeže a TělovýchovyCZ.02.1.01/0.0/0.0/16_026/0008404
Ministerstvo Školství, Mládeže a Tělovýchovy
Engineering and Physical Sciences Research CouncilEP/V055011/1
Engineering and Physical Sciences Research Council

Keywords

  • Surface integrity
  • machining
  • Sensor
  • sensors
  • On-machine measurement (OMM)
  • In-process measurement
  • Monitoring
  • Control

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