Determination of a coupling equation for milling parameters based on optimal cutting temperature
Abstract The optimization of cutting parameters has a great concern in the field of manufacturing process, especially the relationships among cutting parameters, with the study aiming at exploring a coupling equation to cutting parameters based on the optimal cutting temperature in the milling proce...
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| Autor*in: |
Sheng, Jing [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag London 2017 |
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| Übergeordnetes Werk: |
Enthalten in: The international journal of advanced manufacturing technology - London : Springer, 1985, 98(2017), 1-4 vom: 27. Mai, Seite 129-141 |
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| Übergeordnetes Werk: |
volume:98 ; year:2017 ; number:1-4 ; day:27 ; month:05 ; pages:129-141 |
| Links: |
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| DOI / URN: |
10.1007/s00170-017-0542-4 |
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| Katalog-ID: |
SPR001477498 |
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| 245 | 1 | 0 | |a Determination of a coupling equation for milling parameters based on optimal cutting temperature |
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| 520 | |a Abstract The optimization of cutting parameters has a great concern in the field of manufacturing process, especially the relationships among cutting parameters, with the study aiming at exploring a coupling equation to cutting parameters based on the optimal cutting temperature in the milling process of precipitation-hardening stainless steel with cemented carbide inserts. Initially, the association among the ratios of cutting tool wear of the machined surface, the cutting speed, and temperature was respectively investigated, with the ratio also used as an evaluating level of tool wear. Afterwards, the effects of the work hardening layer depth and the work hardening degree on the cutting speed and temperature were discussed in order to evaluate the machined surface quality. The results indicate that while the minimum tool wear occurred, the tool tip temperature at the cutting zone stayed the same with the minimum degree of work hardening appearing, which was defined as the optimal cutting temperature. An empirical formula for the cutting temperature and cutting parameters is explored using regression orthogonal experiment design, and then combined with optimum temperature. As a result, a coupling equation to cutting parameters is determined. Meanwhile, the mechanism of the minimal cutter wear is analyzed in accordance with the characteristics of cutting tool wear under several different machining conditions. The coupling equation could be put into an optimization model as a constraint. The results of this research would be beneficial to application of cooling liquids and cooling method to achieve cleaner production as well as the construction of a cutting database of metal materials. | ||
| 650 | 4 | |a Cutting tool wear |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Cutting temperature |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Coupling equation for milling parameters |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Orthogonal experiments |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Cutting parameter optimization equation |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Chiu, Yi-Jui |4 aut | |
| 700 | 1 | |a Lin, Bing-Jing |4 aut | |
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10.1007/s00170-017-0542-4 doi (DE-627)SPR001477498 (SPR)s00170-017-0542-4-e DE-627 ger DE-627 rakwb eng Sheng, Jing verfasserin aut Determination of a coupling equation for milling parameters based on optimal cutting temperature 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London 2017 Abstract The optimization of cutting parameters has a great concern in the field of manufacturing process, especially the relationships among cutting parameters, with the study aiming at exploring a coupling equation to cutting parameters based on the optimal cutting temperature in the milling process of precipitation-hardening stainless steel with cemented carbide inserts. Initially, the association among the ratios of cutting tool wear of the machined surface, the cutting speed, and temperature was respectively investigated, with the ratio also used as an evaluating level of tool wear. Afterwards, the effects of the work hardening layer depth and the work hardening degree on the cutting speed and temperature were discussed in order to evaluate the machined surface quality. The results indicate that while the minimum tool wear occurred, the tool tip temperature at the cutting zone stayed the same with the minimum degree of work hardening appearing, which was defined as the optimal cutting temperature. An empirical formula for the cutting temperature and cutting parameters is explored using regression orthogonal experiment design, and then combined with optimum temperature. As a result, a coupling equation to cutting parameters is determined. Meanwhile, the mechanism of the minimal cutter wear is analyzed in accordance with the characteristics of cutting tool wear under several different machining conditions. The coupling equation could be put into an optimization model as a constraint. The results of this research would be beneficial to application of cooling liquids and cooling method to achieve cleaner production as well as the construction of a cutting database of metal materials. Cutting tool wear (dpeaa)DE-He213 Cutting temperature (dpeaa)DE-He213 Coupling equation for milling parameters (dpeaa)DE-He213 Orthogonal experiments (dpeaa)DE-He213 Cutting parameter optimization equation (dpeaa)DE-He213 Chiu, Yi-Jui aut Lin, Bing-Jing aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 98(2017), 1-4 vom: 27. Mai, Seite 129-141 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:98 year:2017 number:1-4 day:27 month:05 pages:129-141 https://dx.doi.org/10.1007/s00170-017-0542-4 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_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_206 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_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 98 2017 1-4 27 05 129-141 |
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10.1007/s00170-017-0542-4 doi (DE-627)SPR001477498 (SPR)s00170-017-0542-4-e DE-627 ger DE-627 rakwb eng Sheng, Jing verfasserin aut Determination of a coupling equation for milling parameters based on optimal cutting temperature 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London 2017 Abstract The optimization of cutting parameters has a great concern in the field of manufacturing process, especially the relationships among cutting parameters, with the study aiming at exploring a coupling equation to cutting parameters based on the optimal cutting temperature in the milling process of precipitation-hardening stainless steel with cemented carbide inserts. Initially, the association among the ratios of cutting tool wear of the machined surface, the cutting speed, and temperature was respectively investigated, with the ratio also used as an evaluating level of tool wear. Afterwards, the effects of the work hardening layer depth and the work hardening degree on the cutting speed and temperature were discussed in order to evaluate the machined surface quality. The results indicate that while the minimum tool wear occurred, the tool tip temperature at the cutting zone stayed the same with the minimum degree of work hardening appearing, which was defined as the optimal cutting temperature. An empirical formula for the cutting temperature and cutting parameters is explored using regression orthogonal experiment design, and then combined with optimum temperature. As a result, a coupling equation to cutting parameters is determined. Meanwhile, the mechanism of the minimal cutter wear is analyzed in accordance with the characteristics of cutting tool wear under several different machining conditions. The coupling equation could be put into an optimization model as a constraint. The results of this research would be beneficial to application of cooling liquids and cooling method to achieve cleaner production as well as the construction of a cutting database of metal materials. Cutting tool wear (dpeaa)DE-He213 Cutting temperature (dpeaa)DE-He213 Coupling equation for milling parameters (dpeaa)DE-He213 Orthogonal experiments (dpeaa)DE-He213 Cutting parameter optimization equation (dpeaa)DE-He213 Chiu, Yi-Jui aut Lin, Bing-Jing aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 98(2017), 1-4 vom: 27. Mai, Seite 129-141 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:98 year:2017 number:1-4 day:27 month:05 pages:129-141 https://dx.doi.org/10.1007/s00170-017-0542-4 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_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_206 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_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 98 2017 1-4 27 05 129-141 |
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10.1007/s00170-017-0542-4 doi (DE-627)SPR001477498 (SPR)s00170-017-0542-4-e DE-627 ger DE-627 rakwb eng Sheng, Jing verfasserin aut Determination of a coupling equation for milling parameters based on optimal cutting temperature 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London 2017 Abstract The optimization of cutting parameters has a great concern in the field of manufacturing process, especially the relationships among cutting parameters, with the study aiming at exploring a coupling equation to cutting parameters based on the optimal cutting temperature in the milling process of precipitation-hardening stainless steel with cemented carbide inserts. Initially, the association among the ratios of cutting tool wear of the machined surface, the cutting speed, and temperature was respectively investigated, with the ratio also used as an evaluating level of tool wear. Afterwards, the effects of the work hardening layer depth and the work hardening degree on the cutting speed and temperature were discussed in order to evaluate the machined surface quality. The results indicate that while the minimum tool wear occurred, the tool tip temperature at the cutting zone stayed the same with the minimum degree of work hardening appearing, which was defined as the optimal cutting temperature. An empirical formula for the cutting temperature and cutting parameters is explored using regression orthogonal experiment design, and then combined with optimum temperature. As a result, a coupling equation to cutting parameters is determined. Meanwhile, the mechanism of the minimal cutter wear is analyzed in accordance with the characteristics of cutting tool wear under several different machining conditions. The coupling equation could be put into an optimization model as a constraint. The results of this research would be beneficial to application of cooling liquids and cooling method to achieve cleaner production as well as the construction of a cutting database of metal materials. Cutting tool wear (dpeaa)DE-He213 Cutting temperature (dpeaa)DE-He213 Coupling equation for milling parameters (dpeaa)DE-He213 Orthogonal experiments (dpeaa)DE-He213 Cutting parameter optimization equation (dpeaa)DE-He213 Chiu, Yi-Jui aut Lin, Bing-Jing aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 98(2017), 1-4 vom: 27. Mai, Seite 129-141 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:98 year:2017 number:1-4 day:27 month:05 pages:129-141 https://dx.doi.org/10.1007/s00170-017-0542-4 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_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_206 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_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 98 2017 1-4 27 05 129-141 |
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10.1007/s00170-017-0542-4 doi (DE-627)SPR001477498 (SPR)s00170-017-0542-4-e DE-627 ger DE-627 rakwb eng Sheng, Jing verfasserin aut Determination of a coupling equation for milling parameters based on optimal cutting temperature 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London 2017 Abstract The optimization of cutting parameters has a great concern in the field of manufacturing process, especially the relationships among cutting parameters, with the study aiming at exploring a coupling equation to cutting parameters based on the optimal cutting temperature in the milling process of precipitation-hardening stainless steel with cemented carbide inserts. Initially, the association among the ratios of cutting tool wear of the machined surface, the cutting speed, and temperature was respectively investigated, with the ratio also used as an evaluating level of tool wear. Afterwards, the effects of the work hardening layer depth and the work hardening degree on the cutting speed and temperature were discussed in order to evaluate the machined surface quality. The results indicate that while the minimum tool wear occurred, the tool tip temperature at the cutting zone stayed the same with the minimum degree of work hardening appearing, which was defined as the optimal cutting temperature. An empirical formula for the cutting temperature and cutting parameters is explored using regression orthogonal experiment design, and then combined with optimum temperature. As a result, a coupling equation to cutting parameters is determined. Meanwhile, the mechanism of the minimal cutter wear is analyzed in accordance with the characteristics of cutting tool wear under several different machining conditions. The coupling equation could be put into an optimization model as a constraint. The results of this research would be beneficial to application of cooling liquids and cooling method to achieve cleaner production as well as the construction of a cutting database of metal materials. Cutting tool wear (dpeaa)DE-He213 Cutting temperature (dpeaa)DE-He213 Coupling equation for milling parameters (dpeaa)DE-He213 Orthogonal experiments (dpeaa)DE-He213 Cutting parameter optimization equation (dpeaa)DE-He213 Chiu, Yi-Jui aut Lin, Bing-Jing aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 98(2017), 1-4 vom: 27. Mai, Seite 129-141 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:98 year:2017 number:1-4 day:27 month:05 pages:129-141 https://dx.doi.org/10.1007/s00170-017-0542-4 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_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_206 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_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 98 2017 1-4 27 05 129-141 |
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10.1007/s00170-017-0542-4 doi (DE-627)SPR001477498 (SPR)s00170-017-0542-4-e DE-627 ger DE-627 rakwb eng Sheng, Jing verfasserin aut Determination of a coupling equation for milling parameters based on optimal cutting temperature 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London 2017 Abstract The optimization of cutting parameters has a great concern in the field of manufacturing process, especially the relationships among cutting parameters, with the study aiming at exploring a coupling equation to cutting parameters based on the optimal cutting temperature in the milling process of precipitation-hardening stainless steel with cemented carbide inserts. Initially, the association among the ratios of cutting tool wear of the machined surface, the cutting speed, and temperature was respectively investigated, with the ratio also used as an evaluating level of tool wear. Afterwards, the effects of the work hardening layer depth and the work hardening degree on the cutting speed and temperature were discussed in order to evaluate the machined surface quality. The results indicate that while the minimum tool wear occurred, the tool tip temperature at the cutting zone stayed the same with the minimum degree of work hardening appearing, which was defined as the optimal cutting temperature. An empirical formula for the cutting temperature and cutting parameters is explored using regression orthogonal experiment design, and then combined with optimum temperature. As a result, a coupling equation to cutting parameters is determined. Meanwhile, the mechanism of the minimal cutter wear is analyzed in accordance with the characteristics of cutting tool wear under several different machining conditions. The coupling equation could be put into an optimization model as a constraint. The results of this research would be beneficial to application of cooling liquids and cooling method to achieve cleaner production as well as the construction of a cutting database of metal materials. Cutting tool wear (dpeaa)DE-He213 Cutting temperature (dpeaa)DE-He213 Coupling equation for milling parameters (dpeaa)DE-He213 Orthogonal experiments (dpeaa)DE-He213 Cutting parameter optimization equation (dpeaa)DE-He213 Chiu, Yi-Jui aut Lin, Bing-Jing aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 98(2017), 1-4 vom: 27. Mai, Seite 129-141 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:98 year:2017 number:1-4 day:27 month:05 pages:129-141 https://dx.doi.org/10.1007/s00170-017-0542-4 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_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_206 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_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 98 2017 1-4 27 05 129-141 |
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Initially, the association among the ratios of cutting tool wear of the machined surface, the cutting speed, and temperature was respectively investigated, with the ratio also used as an evaluating level of tool wear. Afterwards, the effects of the work hardening layer depth and the work hardening degree on the cutting speed and temperature were discussed in order to evaluate the machined surface quality. The results indicate that while the minimum tool wear occurred, the tool tip temperature at the cutting zone stayed the same with the minimum degree of work hardening appearing, which was defined as the optimal cutting temperature. An empirical formula for the cutting temperature and cutting parameters is explored using regression orthogonal experiment design, and then combined with optimum temperature. As a result, a coupling equation to cutting parameters is determined. Meanwhile, the mechanism of the minimal cutter wear is analyzed in accordance with the characteristics of cutting tool wear under several different machining conditions. The coupling equation could be put into an optimization model as a constraint. 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Sheng, Jing |
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Sheng, Jing misc Cutting tool wear misc Cutting temperature misc Coupling equation for milling parameters misc Orthogonal experiments misc Cutting parameter optimization equation Determination of a coupling equation for milling parameters based on optimal cutting temperature |
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Determination of a coupling equation for milling parameters based on optimal cutting temperature Cutting tool wear (dpeaa)DE-He213 Cutting temperature (dpeaa)DE-He213 Coupling equation for milling parameters (dpeaa)DE-He213 Orthogonal experiments (dpeaa)DE-He213 Cutting parameter optimization equation (dpeaa)DE-He213 |
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misc Cutting tool wear misc Cutting temperature misc Coupling equation for milling parameters misc Orthogonal experiments misc Cutting parameter optimization equation |
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misc Cutting tool wear misc Cutting temperature misc Coupling equation for milling parameters misc Orthogonal experiments misc Cutting parameter optimization equation |
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Determination of a coupling equation for milling parameters based on optimal cutting temperature |
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determination of a coupling equation for milling parameters based on optimal cutting temperature |
| title_auth |
Determination of a coupling equation for milling parameters based on optimal cutting temperature |
| abstract |
Abstract The optimization of cutting parameters has a great concern in the field of manufacturing process, especially the relationships among cutting parameters, with the study aiming at exploring a coupling equation to cutting parameters based on the optimal cutting temperature in the milling process of precipitation-hardening stainless steel with cemented carbide inserts. Initially, the association among the ratios of cutting tool wear of the machined surface, the cutting speed, and temperature was respectively investigated, with the ratio also used as an evaluating level of tool wear. Afterwards, the effects of the work hardening layer depth and the work hardening degree on the cutting speed and temperature were discussed in order to evaluate the machined surface quality. The results indicate that while the minimum tool wear occurred, the tool tip temperature at the cutting zone stayed the same with the minimum degree of work hardening appearing, which was defined as the optimal cutting temperature. An empirical formula for the cutting temperature and cutting parameters is explored using regression orthogonal experiment design, and then combined with optimum temperature. As a result, a coupling equation to cutting parameters is determined. Meanwhile, the mechanism of the minimal cutter wear is analyzed in accordance with the characteristics of cutting tool wear under several different machining conditions. The coupling equation could be put into an optimization model as a constraint. The results of this research would be beneficial to application of cooling liquids and cooling method to achieve cleaner production as well as the construction of a cutting database of metal materials. © Springer-Verlag London 2017 |
| abstractGer |
Abstract The optimization of cutting parameters has a great concern in the field of manufacturing process, especially the relationships among cutting parameters, with the study aiming at exploring a coupling equation to cutting parameters based on the optimal cutting temperature in the milling process of precipitation-hardening stainless steel with cemented carbide inserts. Initially, the association among the ratios of cutting tool wear of the machined surface, the cutting speed, and temperature was respectively investigated, with the ratio also used as an evaluating level of tool wear. Afterwards, the effects of the work hardening layer depth and the work hardening degree on the cutting speed and temperature were discussed in order to evaluate the machined surface quality. The results indicate that while the minimum tool wear occurred, the tool tip temperature at the cutting zone stayed the same with the minimum degree of work hardening appearing, which was defined as the optimal cutting temperature. An empirical formula for the cutting temperature and cutting parameters is explored using regression orthogonal experiment design, and then combined with optimum temperature. As a result, a coupling equation to cutting parameters is determined. Meanwhile, the mechanism of the minimal cutter wear is analyzed in accordance with the characteristics of cutting tool wear under several different machining conditions. The coupling equation could be put into an optimization model as a constraint. The results of this research would be beneficial to application of cooling liquids and cooling method to achieve cleaner production as well as the construction of a cutting database of metal materials. © Springer-Verlag London 2017 |
| abstract_unstemmed |
Abstract The optimization of cutting parameters has a great concern in the field of manufacturing process, especially the relationships among cutting parameters, with the study aiming at exploring a coupling equation to cutting parameters based on the optimal cutting temperature in the milling process of precipitation-hardening stainless steel with cemented carbide inserts. Initially, the association among the ratios of cutting tool wear of the machined surface, the cutting speed, and temperature was respectively investigated, with the ratio also used as an evaluating level of tool wear. Afterwards, the effects of the work hardening layer depth and the work hardening degree on the cutting speed and temperature were discussed in order to evaluate the machined surface quality. The results indicate that while the minimum tool wear occurred, the tool tip temperature at the cutting zone stayed the same with the minimum degree of work hardening appearing, which was defined as the optimal cutting temperature. An empirical formula for the cutting temperature and cutting parameters is explored using regression orthogonal experiment design, and then combined with optimum temperature. As a result, a coupling equation to cutting parameters is determined. Meanwhile, the mechanism of the minimal cutter wear is analyzed in accordance with the characteristics of cutting tool wear under several different machining conditions. The coupling equation could be put into an optimization model as a constraint. The results of this research would be beneficial to application of cooling liquids and cooling method to achieve cleaner production as well as the construction of a cutting database of metal materials. © Springer-Verlag London 2017 |
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Determination of a coupling equation for milling parameters based on optimal cutting temperature |
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https://dx.doi.org/10.1007/s00170-017-0542-4 |
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Chiu, Yi-Jui Lin, Bing-Jing |
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10.1007/s00170-017-0542-4 |
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|
| score |
7.39812 |