An Investigation into Turning of ASSAB-705 Steel Using Multiple Sensors
The complex behavior of various occurrences in turning has made the tool condition and process monitoring with a conventional tool-sensor setup difficult. An additional passive tool arrangement has been adopted to circumvent the multifaceted mechanism of different occurrences and thus to investigate...
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my.um.eprints.186042018-04-25T06:13:53Z http://eprints.um.edu.my/18604/ An Investigation into Turning of ASSAB-705 Steel Using Multiple Sensors Bhuiyan, M.S.H. Choudhury, I.A. Dahari, M. Nukman, Y. TJ Mechanical engineering and machinery The complex behavior of various occurrences in turning has made the tool condition and process monitoring with a conventional tool-sensor setup difficult. An additional passive tool arrangement has been adopted to circumvent the multifaceted mechanism of different occurrences and thus to investigate them by measuring the acoustic emission (AE), and vibration signals produced thereof. The investigation shows that both the AE and the radial vibration component, Vy can independently assess the chip formation effect on cutting process and tool state. The tangential vibration component, Vz can effectively evaluate the rate of flank wear progression whereas the resultant vibration components are efficient in measuring the surface roughness of workpiece in turning. The feed directional vibration, Vx is always maximal regardless of cutting variables, tool wear, surface roughness, and chip formation type. The application of vibration sensor can eliminate the necessity of the additional passive tool setup, and jointly with the AE sensor can investigate the process and cutting tool condition more promisingly. Marcel Dekker (now owned by Taylor & Francis) 2016 Article PeerReviewed Bhuiyan, M.S.H. and Choudhury, I.A. and Dahari, M. and Nukman, Y. (2016) An Investigation into Turning of ASSAB-705 Steel Using Multiple Sensors. Materials and Manufacturing Processes, 31 (7). pp. 896-904. ISSN 1042-6914 https://doi.org/10.1080/10426914.2015.1048358 doi:10.1080/10426914.2015.1048358 |
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TJ Mechanical engineering and machinery Bhuiyan, M.S.H. Choudhury, I.A. Dahari, M. Nukman, Y. An Investigation into Turning of ASSAB-705 Steel Using Multiple Sensors |
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The complex behavior of various occurrences in turning has made the tool condition and process monitoring with a conventional tool-sensor setup difficult. An additional passive tool arrangement has been adopted to circumvent the multifaceted mechanism of different occurrences and thus to investigate them by measuring the acoustic emission (AE), and vibration signals produced thereof. The investigation shows that both the AE and the radial vibration component, Vy can independently assess the chip formation effect on cutting process and tool state. The tangential vibration component, Vz can effectively evaluate the rate of flank wear progression whereas the resultant vibration components are efficient in measuring the surface roughness of workpiece in turning. The feed directional vibration, Vx is always maximal regardless of cutting variables, tool wear, surface roughness, and chip formation type. The application of vibration sensor can eliminate the necessity of the additional passive tool setup, and jointly with the AE sensor can investigate the process and cutting tool condition more promisingly. |
format |
Article |
author |
Bhuiyan, M.S.H. Choudhury, I.A. Dahari, M. Nukman, Y. |
author_facet |
Bhuiyan, M.S.H. Choudhury, I.A. Dahari, M. Nukman, Y. |
author_sort |
Bhuiyan, M.S.H. |
title |
An Investigation into Turning of ASSAB-705 Steel Using Multiple Sensors |
title_short |
An Investigation into Turning of ASSAB-705 Steel Using Multiple Sensors |
title_full |
An Investigation into Turning of ASSAB-705 Steel Using Multiple Sensors |
title_fullStr |
An Investigation into Turning of ASSAB-705 Steel Using Multiple Sensors |
title_full_unstemmed |
An Investigation into Turning of ASSAB-705 Steel Using Multiple Sensors |
title_sort |
investigation into turning of assab-705 steel using multiple sensors |
publisher |
Marcel Dekker (now owned by Taylor & Francis) |
publishDate |
2016 |
url |
http://eprints.um.edu.my/18604/ https://doi.org/10.1080/10426914.2015.1048358 |
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1643690741896052736 |
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13.211869 |