Analysis of Tool Wear by Using a Cutting Bending Moment Model for Milling Processes
Abstract In this study, we developed a bending moment model that considers the cutting forces acting on a sensory tool holder along the rotational direction. The polar plot of the bending moment during cutting can be used to investigate the cutting behavior. Cutting processes with different cutting...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Tseng, Hsiang-Chun [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Korean Society for Precision Engineering 2022 |
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| Übergeordnetes Werk: |
Enthalten in: International journal of precision engineering and manufacturing - Sŏul : KSPE, 2009, 23(2022), 8 vom: 21. Juni, Seite 943-955 |
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| Übergeordnetes Werk: |
volume:23 ; year:2022 ; number:8 ; day:21 ; month:06 ; pages:943-955 |
| Links: |
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| DOI / URN: |
10.1007/s12541-022-00680-9 |
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| Katalog-ID: |
SPR050911635 |
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| 100 | 1 | |a Tseng, Hsiang-Chun |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Analysis of Tool Wear by Using a Cutting Bending Moment Model for Milling Processes |
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| 520 | |a Abstract In this study, we developed a bending moment model that considers the cutting forces acting on a sensory tool holder along the rotational direction. The polar plot of the bending moment during cutting can be used to investigate the cutting behavior. Cutting processes with different cutting depths and widths result in different polar plots, as verified experimentally. To evaluate the effect of tool wear on the polar plot, the bending moment equations were modified to incorporate the developed tool wear model. The simulation results indicated that tool wear can increase the size of the polar plot and vary the angle of the plot. By examining the change of this angle, one can determine the level of tool wear. The experimental results of this study indicated that the derived equation can predict the tool wear behavior with an average accuracy of 84%. Thus, the proposed integrated model enables the accurate prediction of tool wear. Consequently, the polar plot can feasibly be used to detect the level of tool wear. | ||
| 650 | 4 | |a Cutting bending moment |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a End milling |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Tool monitoring |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Tool wear |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Tsai, Meng-Shiun |4 aut | |
| 700 | 1 | |a Yeh, Bu-Ci |4 aut | |
| 700 | 1 | |a Li, Kuan-Ming |4 aut | |
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10.1007/s12541-022-00680-9 doi (DE-627)SPR050911635 (SPR)s12541-022-00680-9-e DE-627 ger DE-627 rakwb eng Tseng, Hsiang-Chun verfasserin aut Analysis of Tool Wear by Using a Cutting Bending Moment Model for Milling Processes 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Korean Society for Precision Engineering 2022 Abstract In this study, we developed a bending moment model that considers the cutting forces acting on a sensory tool holder along the rotational direction. The polar plot of the bending moment during cutting can be used to investigate the cutting behavior. Cutting processes with different cutting depths and widths result in different polar plots, as verified experimentally. To evaluate the effect of tool wear on the polar plot, the bending moment equations were modified to incorporate the developed tool wear model. The simulation results indicated that tool wear can increase the size of the polar plot and vary the angle of the plot. By examining the change of this angle, one can determine the level of tool wear. The experimental results of this study indicated that the derived equation can predict the tool wear behavior with an average accuracy of 84%. Thus, the proposed integrated model enables the accurate prediction of tool wear. Consequently, the polar plot can feasibly be used to detect the level of tool wear. Cutting bending moment (dpeaa)DE-He213 End milling (dpeaa)DE-He213 Tool monitoring (dpeaa)DE-He213 Tool wear (dpeaa)DE-He213 Tsai, Meng-Shiun aut Yeh, Bu-Ci aut Li, Kuan-Ming aut Enthalten in International journal of precision engineering and manufacturing Sŏul : KSPE, 2009 23(2022), 8 vom: 21. Juni, Seite 943-955 (DE-627)609403109 (DE-600)2515436-9 2005-4602 nnns volume:23 year:2022 number:8 day:21 month:06 pages:943-955 https://dx.doi.org/10.1007/s12541-022-00680-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 23 2022 8 21 06 943-955 |
| spelling |
10.1007/s12541-022-00680-9 doi (DE-627)SPR050911635 (SPR)s12541-022-00680-9-e DE-627 ger DE-627 rakwb eng Tseng, Hsiang-Chun verfasserin aut Analysis of Tool Wear by Using a Cutting Bending Moment Model for Milling Processes 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Korean Society for Precision Engineering 2022 Abstract In this study, we developed a bending moment model that considers the cutting forces acting on a sensory tool holder along the rotational direction. The polar plot of the bending moment during cutting can be used to investigate the cutting behavior. Cutting processes with different cutting depths and widths result in different polar plots, as verified experimentally. To evaluate the effect of tool wear on the polar plot, the bending moment equations were modified to incorporate the developed tool wear model. The simulation results indicated that tool wear can increase the size of the polar plot and vary the angle of the plot. By examining the change of this angle, one can determine the level of tool wear. The experimental results of this study indicated that the derived equation can predict the tool wear behavior with an average accuracy of 84%. Thus, the proposed integrated model enables the accurate prediction of tool wear. Consequently, the polar plot can feasibly be used to detect the level of tool wear. Cutting bending moment (dpeaa)DE-He213 End milling (dpeaa)DE-He213 Tool monitoring (dpeaa)DE-He213 Tool wear (dpeaa)DE-He213 Tsai, Meng-Shiun aut Yeh, Bu-Ci aut Li, Kuan-Ming aut Enthalten in International journal of precision engineering and manufacturing Sŏul : KSPE, 2009 23(2022), 8 vom: 21. Juni, Seite 943-955 (DE-627)609403109 (DE-600)2515436-9 2005-4602 nnns volume:23 year:2022 number:8 day:21 month:06 pages:943-955 https://dx.doi.org/10.1007/s12541-022-00680-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 23 2022 8 21 06 943-955 |
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10.1007/s12541-022-00680-9 doi (DE-627)SPR050911635 (SPR)s12541-022-00680-9-e DE-627 ger DE-627 rakwb eng Tseng, Hsiang-Chun verfasserin aut Analysis of Tool Wear by Using a Cutting Bending Moment Model for Milling Processes 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Korean Society for Precision Engineering 2022 Abstract In this study, we developed a bending moment model that considers the cutting forces acting on a sensory tool holder along the rotational direction. The polar plot of the bending moment during cutting can be used to investigate the cutting behavior. Cutting processes with different cutting depths and widths result in different polar plots, as verified experimentally. To evaluate the effect of tool wear on the polar plot, the bending moment equations were modified to incorporate the developed tool wear model. The simulation results indicated that tool wear can increase the size of the polar plot and vary the angle of the plot. By examining the change of this angle, one can determine the level of tool wear. The experimental results of this study indicated that the derived equation can predict the tool wear behavior with an average accuracy of 84%. Thus, the proposed integrated model enables the accurate prediction of tool wear. Consequently, the polar plot can feasibly be used to detect the level of tool wear. Cutting bending moment (dpeaa)DE-He213 End milling (dpeaa)DE-He213 Tool monitoring (dpeaa)DE-He213 Tool wear (dpeaa)DE-He213 Tsai, Meng-Shiun aut Yeh, Bu-Ci aut Li, Kuan-Ming aut Enthalten in International journal of precision engineering and manufacturing Sŏul : KSPE, 2009 23(2022), 8 vom: 21. Juni, Seite 943-955 (DE-627)609403109 (DE-600)2515436-9 2005-4602 nnns volume:23 year:2022 number:8 day:21 month:06 pages:943-955 https://dx.doi.org/10.1007/s12541-022-00680-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 23 2022 8 21 06 943-955 |
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10.1007/s12541-022-00680-9 doi (DE-627)SPR050911635 (SPR)s12541-022-00680-9-e DE-627 ger DE-627 rakwb eng Tseng, Hsiang-Chun verfasserin aut Analysis of Tool Wear by Using a Cutting Bending Moment Model for Milling Processes 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Korean Society for Precision Engineering 2022 Abstract In this study, we developed a bending moment model that considers the cutting forces acting on a sensory tool holder along the rotational direction. The polar plot of the bending moment during cutting can be used to investigate the cutting behavior. Cutting processes with different cutting depths and widths result in different polar plots, as verified experimentally. To evaluate the effect of tool wear on the polar plot, the bending moment equations were modified to incorporate the developed tool wear model. The simulation results indicated that tool wear can increase the size of the polar plot and vary the angle of the plot. By examining the change of this angle, one can determine the level of tool wear. The experimental results of this study indicated that the derived equation can predict the tool wear behavior with an average accuracy of 84%. Thus, the proposed integrated model enables the accurate prediction of tool wear. Consequently, the polar plot can feasibly be used to detect the level of tool wear. Cutting bending moment (dpeaa)DE-He213 End milling (dpeaa)DE-He213 Tool monitoring (dpeaa)DE-He213 Tool wear (dpeaa)DE-He213 Tsai, Meng-Shiun aut Yeh, Bu-Ci aut Li, Kuan-Ming aut Enthalten in International journal of precision engineering and manufacturing Sŏul : KSPE, 2009 23(2022), 8 vom: 21. Juni, Seite 943-955 (DE-627)609403109 (DE-600)2515436-9 2005-4602 nnns volume:23 year:2022 number:8 day:21 month:06 pages:943-955 https://dx.doi.org/10.1007/s12541-022-00680-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 23 2022 8 21 06 943-955 |
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10.1007/s12541-022-00680-9 doi (DE-627)SPR050911635 (SPR)s12541-022-00680-9-e DE-627 ger DE-627 rakwb eng Tseng, Hsiang-Chun verfasserin aut Analysis of Tool Wear by Using a Cutting Bending Moment Model for Milling Processes 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Korean Society for Precision Engineering 2022 Abstract In this study, we developed a bending moment model that considers the cutting forces acting on a sensory tool holder along the rotational direction. The polar plot of the bending moment during cutting can be used to investigate the cutting behavior. Cutting processes with different cutting depths and widths result in different polar plots, as verified experimentally. To evaluate the effect of tool wear on the polar plot, the bending moment equations were modified to incorporate the developed tool wear model. The simulation results indicated that tool wear can increase the size of the polar plot and vary the angle of the plot. By examining the change of this angle, one can determine the level of tool wear. The experimental results of this study indicated that the derived equation can predict the tool wear behavior with an average accuracy of 84%. Thus, the proposed integrated model enables the accurate prediction of tool wear. Consequently, the polar plot can feasibly be used to detect the level of tool wear. Cutting bending moment (dpeaa)DE-He213 End milling (dpeaa)DE-He213 Tool monitoring (dpeaa)DE-He213 Tool wear (dpeaa)DE-He213 Tsai, Meng-Shiun aut Yeh, Bu-Ci aut Li, Kuan-Ming aut Enthalten in International journal of precision engineering and manufacturing Sŏul : KSPE, 2009 23(2022), 8 vom: 21. Juni, Seite 943-955 (DE-627)609403109 (DE-600)2515436-9 2005-4602 nnns volume:23 year:2022 number:8 day:21 month:06 pages:943-955 https://dx.doi.org/10.1007/s12541-022-00680-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 23 2022 8 21 06 943-955 |
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Tseng, Hsiang-Chun |
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Tseng, Hsiang-Chun misc Cutting bending moment misc End milling misc Tool monitoring misc Tool wear Analysis of Tool Wear by Using a Cutting Bending Moment Model for Milling Processes |
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Analysis of Tool Wear by Using a Cutting Bending Moment Model for Milling Processes Cutting bending moment (dpeaa)DE-He213 End milling (dpeaa)DE-He213 Tool monitoring (dpeaa)DE-He213 Tool wear (dpeaa)DE-He213 |
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misc Cutting bending moment misc End milling misc Tool monitoring misc Tool wear |
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Analysis of Tool Wear by Using a Cutting Bending Moment Model for Milling Processes |
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Analysis of Tool Wear by Using a Cutting Bending Moment Model for Milling Processes |
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analysis of tool wear by using a cutting bending moment model for milling processes |
| title_auth |
Analysis of Tool Wear by Using a Cutting Bending Moment Model for Milling Processes |
| abstract |
Abstract In this study, we developed a bending moment model that considers the cutting forces acting on a sensory tool holder along the rotational direction. The polar plot of the bending moment during cutting can be used to investigate the cutting behavior. Cutting processes with different cutting depths and widths result in different polar plots, as verified experimentally. To evaluate the effect of tool wear on the polar plot, the bending moment equations were modified to incorporate the developed tool wear model. The simulation results indicated that tool wear can increase the size of the polar plot and vary the angle of the plot. By examining the change of this angle, one can determine the level of tool wear. The experimental results of this study indicated that the derived equation can predict the tool wear behavior with an average accuracy of 84%. Thus, the proposed integrated model enables the accurate prediction of tool wear. Consequently, the polar plot can feasibly be used to detect the level of tool wear. © The Author(s), under exclusive licence to Korean Society for Precision Engineering 2022 |
| abstractGer |
Abstract In this study, we developed a bending moment model that considers the cutting forces acting on a sensory tool holder along the rotational direction. The polar plot of the bending moment during cutting can be used to investigate the cutting behavior. Cutting processes with different cutting depths and widths result in different polar plots, as verified experimentally. To evaluate the effect of tool wear on the polar plot, the bending moment equations were modified to incorporate the developed tool wear model. The simulation results indicated that tool wear can increase the size of the polar plot and vary the angle of the plot. By examining the change of this angle, one can determine the level of tool wear. The experimental results of this study indicated that the derived equation can predict the tool wear behavior with an average accuracy of 84%. Thus, the proposed integrated model enables the accurate prediction of tool wear. Consequently, the polar plot can feasibly be used to detect the level of tool wear. © The Author(s), under exclusive licence to Korean Society for Precision Engineering 2022 |
| abstract_unstemmed |
Abstract In this study, we developed a bending moment model that considers the cutting forces acting on a sensory tool holder along the rotational direction. The polar plot of the bending moment during cutting can be used to investigate the cutting behavior. Cutting processes with different cutting depths and widths result in different polar plots, as verified experimentally. To evaluate the effect of tool wear on the polar plot, the bending moment equations were modified to incorporate the developed tool wear model. The simulation results indicated that tool wear can increase the size of the polar plot and vary the angle of the plot. By examining the change of this angle, one can determine the level of tool wear. The experimental results of this study indicated that the derived equation can predict the tool wear behavior with an average accuracy of 84%. Thus, the proposed integrated model enables the accurate prediction of tool wear. Consequently, the polar plot can feasibly be used to detect the level of tool wear. © The Author(s), under exclusive licence to Korean Society for Precision Engineering 2022 |
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Analysis of Tool Wear by Using a Cutting Bending Moment Model for Milling Processes |
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https://dx.doi.org/10.1007/s12541-022-00680-9 |
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Tsai, Meng-Shiun Yeh, Bu-Ci Li, Kuan-Ming |
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2024-07-03T18:34:45.368Z |
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