A Sewing Line Planning Model Based on RFID Technology
Abstract Sewing line is one of assembly lines in manufacturing systems in which a product is assembled progressively in workstations by different workers or machines, each executing a subset of the needed assembly tasks. Usually sewing line planning is based on experts’ evaluation of each procedure...
Ausführliche Beschreibung
Autor*in: |
Fu, Xiaokang [verfasserIn] Zou, Jiangbo [verfasserIn] Ju, Chunhua [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2020 |
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Schlagwörter: |
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Übergeordnetes Werk: |
Enthalten in: Journal of electrical engineering & technology - [Singapore] : Springer Singapore, 2006, 15(2020), 3 vom: 14. Apr., Seite 1441-1452 |
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Übergeordnetes Werk: |
volume:15 ; year:2020 ; number:3 ; day:14 ; month:04 ; pages:1441-1452 |
Links: |
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DOI / URN: |
10.1007/s42835-020-00420-x |
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Katalog-ID: |
SPR039669564 |
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520 | |a Abstract Sewing line is one of assembly lines in manufacturing systems in which a product is assembled progressively in workstations by different workers or machines, each executing a subset of the needed assembly tasks. Usually sewing line planning is based on experts’ evaluation of each procedure subjectively, leading to unnecessarily waiting time. To address this issue, in this article we propose a new model named adjustable sewing line planning (ASLP) model, in which both experts’ evaluated data and real-time data are leveraged to improve the line balance timely, along with a RFID based framework and a quadratic-selection genetic algorithm which are designed for line balance optimization. By conducting experiment on one of the largest garment manufacturing companies the model, it can be found from the results that the proposed model is efficient and promising. | ||
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10.1007/s42835-020-00420-x doi (DE-627)SPR039669564 (SPR)s42835-020-00420-x-e DE-627 ger DE-627 rakwb eng 620 ASE 620 ASE Fu, Xiaokang verfasserin aut A Sewing Line Planning Model Based on RFID Technology 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Sewing line is one of assembly lines in manufacturing systems in which a product is assembled progressively in workstations by different workers or machines, each executing a subset of the needed assembly tasks. Usually sewing line planning is based on experts’ evaluation of each procedure subjectively, leading to unnecessarily waiting time. To address this issue, in this article we propose a new model named adjustable sewing line planning (ASLP) model, in which both experts’ evaluated data and real-time data are leveraged to improve the line balance timely, along with a RFID based framework and a quadratic-selection genetic algorithm which are designed for line balance optimization. By conducting experiment on one of the largest garment manufacturing companies the model, it can be found from the results that the proposed model is efficient and promising. Sewing line (dpeaa)DE-He213 Line balance problem (dpeaa)DE-He213 Genetic algorithm (dpeaa)DE-He213 RFID (dpeaa)DE-He213 Balance problems (dpeaa)DE-He213 Zou, Jiangbo verfasserin aut Ju, Chunhua verfasserin aut Enthalten in Journal of electrical engineering & technology [Singapore] : Springer Singapore, 2006 15(2020), 3 vom: 14. Apr., Seite 1441-1452 (DE-627)519202015 (DE-600)2255142-6 2093-7423 nnns volume:15 year:2020 number:3 day:14 month:04 pages:1441-1452 https://dx.doi.org/10.1007/s42835-020-00420-x 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_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 15 2020 3 14 04 1441-1452 |
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10.1007/s42835-020-00420-x doi (DE-627)SPR039669564 (SPR)s42835-020-00420-x-e DE-627 ger DE-627 rakwb eng 620 ASE 620 ASE Fu, Xiaokang verfasserin aut A Sewing Line Planning Model Based on RFID Technology 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Sewing line is one of assembly lines in manufacturing systems in which a product is assembled progressively in workstations by different workers or machines, each executing a subset of the needed assembly tasks. Usually sewing line planning is based on experts’ evaluation of each procedure subjectively, leading to unnecessarily waiting time. To address this issue, in this article we propose a new model named adjustable sewing line planning (ASLP) model, in which both experts’ evaluated data and real-time data are leveraged to improve the line balance timely, along with a RFID based framework and a quadratic-selection genetic algorithm which are designed for line balance optimization. By conducting experiment on one of the largest garment manufacturing companies the model, it can be found from the results that the proposed model is efficient and promising. Sewing line (dpeaa)DE-He213 Line balance problem (dpeaa)DE-He213 Genetic algorithm (dpeaa)DE-He213 RFID (dpeaa)DE-He213 Balance problems (dpeaa)DE-He213 Zou, Jiangbo verfasserin aut Ju, Chunhua verfasserin aut Enthalten in Journal of electrical engineering & technology [Singapore] : Springer Singapore, 2006 15(2020), 3 vom: 14. Apr., Seite 1441-1452 (DE-627)519202015 (DE-600)2255142-6 2093-7423 nnns volume:15 year:2020 number:3 day:14 month:04 pages:1441-1452 https://dx.doi.org/10.1007/s42835-020-00420-x 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_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 15 2020 3 14 04 1441-1452 |
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10.1007/s42835-020-00420-x doi (DE-627)SPR039669564 (SPR)s42835-020-00420-x-e DE-627 ger DE-627 rakwb eng 620 ASE 620 ASE Fu, Xiaokang verfasserin aut A Sewing Line Planning Model Based on RFID Technology 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Sewing line is one of assembly lines in manufacturing systems in which a product is assembled progressively in workstations by different workers or machines, each executing a subset of the needed assembly tasks. Usually sewing line planning is based on experts’ evaluation of each procedure subjectively, leading to unnecessarily waiting time. To address this issue, in this article we propose a new model named adjustable sewing line planning (ASLP) model, in which both experts’ evaluated data and real-time data are leveraged to improve the line balance timely, along with a RFID based framework and a quadratic-selection genetic algorithm which are designed for line balance optimization. By conducting experiment on one of the largest garment manufacturing companies the model, it can be found from the results that the proposed model is efficient and promising. Sewing line (dpeaa)DE-He213 Line balance problem (dpeaa)DE-He213 Genetic algorithm (dpeaa)DE-He213 RFID (dpeaa)DE-He213 Balance problems (dpeaa)DE-He213 Zou, Jiangbo verfasserin aut Ju, Chunhua verfasserin aut Enthalten in Journal of electrical engineering & technology [Singapore] : Springer Singapore, 2006 15(2020), 3 vom: 14. Apr., Seite 1441-1452 (DE-627)519202015 (DE-600)2255142-6 2093-7423 nnns volume:15 year:2020 number:3 day:14 month:04 pages:1441-1452 https://dx.doi.org/10.1007/s42835-020-00420-x 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_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 15 2020 3 14 04 1441-1452 |
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10.1007/s42835-020-00420-x doi (DE-627)SPR039669564 (SPR)s42835-020-00420-x-e DE-627 ger DE-627 rakwb eng 620 ASE 620 ASE Fu, Xiaokang verfasserin aut A Sewing Line Planning Model Based on RFID Technology 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Sewing line is one of assembly lines in manufacturing systems in which a product is assembled progressively in workstations by different workers or machines, each executing a subset of the needed assembly tasks. Usually sewing line planning is based on experts’ evaluation of each procedure subjectively, leading to unnecessarily waiting time. To address this issue, in this article we propose a new model named adjustable sewing line planning (ASLP) model, in which both experts’ evaluated data and real-time data are leveraged to improve the line balance timely, along with a RFID based framework and a quadratic-selection genetic algorithm which are designed for line balance optimization. By conducting experiment on one of the largest garment manufacturing companies the model, it can be found from the results that the proposed model is efficient and promising. Sewing line (dpeaa)DE-He213 Line balance problem (dpeaa)DE-He213 Genetic algorithm (dpeaa)DE-He213 RFID (dpeaa)DE-He213 Balance problems (dpeaa)DE-He213 Zou, Jiangbo verfasserin aut Ju, Chunhua verfasserin aut Enthalten in Journal of electrical engineering & technology [Singapore] : Springer Singapore, 2006 15(2020), 3 vom: 14. Apr., Seite 1441-1452 (DE-627)519202015 (DE-600)2255142-6 2093-7423 nnns volume:15 year:2020 number:3 day:14 month:04 pages:1441-1452 https://dx.doi.org/10.1007/s42835-020-00420-x 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_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 15 2020 3 14 04 1441-1452 |
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10.1007/s42835-020-00420-x doi (DE-627)SPR039669564 (SPR)s42835-020-00420-x-e DE-627 ger DE-627 rakwb eng 620 ASE 620 ASE Fu, Xiaokang verfasserin aut A Sewing Line Planning Model Based on RFID Technology 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Sewing line is one of assembly lines in manufacturing systems in which a product is assembled progressively in workstations by different workers or machines, each executing a subset of the needed assembly tasks. Usually sewing line planning is based on experts’ evaluation of each procedure subjectively, leading to unnecessarily waiting time. To address this issue, in this article we propose a new model named adjustable sewing line planning (ASLP) model, in which both experts’ evaluated data and real-time data are leveraged to improve the line balance timely, along with a RFID based framework and a quadratic-selection genetic algorithm which are designed for line balance optimization. By conducting experiment on one of the largest garment manufacturing companies the model, it can be found from the results that the proposed model is efficient and promising. Sewing line (dpeaa)DE-He213 Line balance problem (dpeaa)DE-He213 Genetic algorithm (dpeaa)DE-He213 RFID (dpeaa)DE-He213 Balance problems (dpeaa)DE-He213 Zou, Jiangbo verfasserin aut Ju, Chunhua verfasserin aut Enthalten in Journal of electrical engineering & technology [Singapore] : Springer Singapore, 2006 15(2020), 3 vom: 14. Apr., Seite 1441-1452 (DE-627)519202015 (DE-600)2255142-6 2093-7423 nnns volume:15 year:2020 number:3 day:14 month:04 pages:1441-1452 https://dx.doi.org/10.1007/s42835-020-00420-x 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_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 15 2020 3 14 04 1441-1452 |
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Fu, Xiaokang @@aut@@ Zou, Jiangbo @@aut@@ Ju, Chunhua @@aut@@ |
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Fu, Xiaokang ddc 620 misc Sewing line misc Line balance problem misc Genetic algorithm misc RFID misc Balance problems A Sewing Line Planning Model Based on RFID Technology |
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620 ASE A Sewing Line Planning Model Based on RFID Technology Sewing line (dpeaa)DE-He213 Line balance problem (dpeaa)DE-He213 Genetic algorithm (dpeaa)DE-He213 RFID (dpeaa)DE-He213 Balance problems (dpeaa)DE-He213 |
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A Sewing Line Planning Model Based on RFID Technology |
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A Sewing Line Planning Model Based on RFID Technology |
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Fu, Xiaokang Zou, Jiangbo Ju, Chunhua |
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sewing line planning model based on rfid technology |
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A Sewing Line Planning Model Based on RFID Technology |
abstract |
Abstract Sewing line is one of assembly lines in manufacturing systems in which a product is assembled progressively in workstations by different workers or machines, each executing a subset of the needed assembly tasks. Usually sewing line planning is based on experts’ evaluation of each procedure subjectively, leading to unnecessarily waiting time. To address this issue, in this article we propose a new model named adjustable sewing line planning (ASLP) model, in which both experts’ evaluated data and real-time data are leveraged to improve the line balance timely, along with a RFID based framework and a quadratic-selection genetic algorithm which are designed for line balance optimization. By conducting experiment on one of the largest garment manufacturing companies the model, it can be found from the results that the proposed model is efficient and promising. |
abstractGer |
Abstract Sewing line is one of assembly lines in manufacturing systems in which a product is assembled progressively in workstations by different workers or machines, each executing a subset of the needed assembly tasks. Usually sewing line planning is based on experts’ evaluation of each procedure subjectively, leading to unnecessarily waiting time. To address this issue, in this article we propose a new model named adjustable sewing line planning (ASLP) model, in which both experts’ evaluated data and real-time data are leveraged to improve the line balance timely, along with a RFID based framework and a quadratic-selection genetic algorithm which are designed for line balance optimization. By conducting experiment on one of the largest garment manufacturing companies the model, it can be found from the results that the proposed model is efficient and promising. |
abstract_unstemmed |
Abstract Sewing line is one of assembly lines in manufacturing systems in which a product is assembled progressively in workstations by different workers or machines, each executing a subset of the needed assembly tasks. Usually sewing line planning is based on experts’ evaluation of each procedure subjectively, leading to unnecessarily waiting time. To address this issue, in this article we propose a new model named adjustable sewing line planning (ASLP) model, in which both experts’ evaluated data and real-time data are leveraged to improve the line balance timely, along with a RFID based framework and a quadratic-selection genetic algorithm which are designed for line balance optimization. By conducting experiment on one of the largest garment manufacturing companies the model, it can be found from the results that the proposed model is efficient and promising. |
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A Sewing Line Planning Model Based on RFID Technology |
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Usually sewing line planning is based on experts’ evaluation of each procedure subjectively, leading to unnecessarily waiting time. To address this issue, in this article we propose a new model named adjustable sewing line planning (ASLP) model, in which both experts’ evaluated data and real-time data are leveraged to improve the line balance timely, along with a RFID based framework and a quadratic-selection genetic algorithm which are designed for line balance optimization. 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