Relevant factors for the energy consumption of industrial robots
Abstract This work investigates the energy consumption of industrial robots in the context of automotive industry. The purpose is to identify the most influencing parameters and variables and to propose best practices with focus on energy efficiency. The analysis approach is composed of three experi...
Ausführliche Beschreibung
Autor*in: |
Garcia, Raphael Rustici [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2018 |
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Schlagwörter: |
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Anmerkung: |
© The Brazilian Society of Mechanical Sciences and Engineering 2018 |
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Übergeordnetes Werk: |
Enthalten in: Journal of the Brazilian Society of Mechanical Sciences and Engineering - Berlin : Springer, 2003, 40(2018), 9 vom: 03. Sept. |
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Übergeordnetes Werk: |
volume:40 ; year:2018 ; number:9 ; day:03 ; month:09 |
Links: |
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DOI / URN: |
10.1007/s40430-018-1376-1 |
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Katalog-ID: |
SPR03646158X |
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520 | |a Abstract This work investigates the energy consumption of industrial robots in the context of automotive industry. The purpose is to identify the most influencing parameters and variables and to propose best practices with focus on energy efficiency. The analysis approach is composed of three experiments performed in a simulation environment that test different values of programming parameters and variables, such as joint speed, acceleration, robot payload. The first experiment focuses on energy consumption of robots at standstill. The second one considers the robot moving along different paths. Finally, the third one analyses how the joint friction is affected by load, speed and temperature and how it influences the energy consumption. Results show that at standstill, it is important to reduce dwell time, select an energy efficient position and reduce the programmed value of the timer responsible for turning off the servomotors. While moving, it is important to select maximum continuous termination for intermediate points and avoid low speeds. Regarding friction variation, results show that at high motor speed, low temperatures increase energy consumption. In order to evaluate the contribution of the best practices in a real environment, they are applied to a welding robotic cell of an automotive industry. | ||
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10.1007/s40430-018-1376-1 doi (DE-627)SPR03646158X (SPR)s40430-018-1376-1-e DE-627 ger DE-627 rakwb eng Garcia, Raphael Rustici verfasserin aut Relevant factors for the energy consumption of industrial robots 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Brazilian Society of Mechanical Sciences and Engineering 2018 Abstract This work investigates the energy consumption of industrial robots in the context of automotive industry. The purpose is to identify the most influencing parameters and variables and to propose best practices with focus on energy efficiency. The analysis approach is composed of three experiments performed in a simulation environment that test different values of programming parameters and variables, such as joint speed, acceleration, robot payload. The first experiment focuses on energy consumption of robots at standstill. The second one considers the robot moving along different paths. Finally, the third one analyses how the joint friction is affected by load, speed and temperature and how it influences the energy consumption. Results show that at standstill, it is important to reduce dwell time, select an energy efficient position and reduce the programmed value of the timer responsible for turning off the servomotors. While moving, it is important to select maximum continuous termination for intermediate points and avoid low speeds. Regarding friction variation, results show that at high motor speed, low temperatures increase energy consumption. In order to evaluate the contribution of the best practices in a real environment, they are applied to a welding robotic cell of an automotive industry. Energy consumption (dpeaa)DE-He213 Industrial robots (dpeaa)DE-He213 Friction modelling (dpeaa)DE-He213 Automotive industry (dpeaa)DE-He213 Bittencourt, André Carvalho aut Villani, Emilia (orcid)0000-0002-6804-1453 aut Enthalten in Journal of the Brazilian Society of Mechanical Sciences and Engineering Berlin : Springer, 2003 40(2018), 9 vom: 03. Sept. (DE-627)387477950 (DE-600)2145288-X 1806-3691 nnns volume:40 year:2018 number:9 day:03 month:09 https://dx.doi.org/10.1007/s40430-018-1376-1 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_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_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 40 2018 9 03 09 |
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10.1007/s40430-018-1376-1 doi (DE-627)SPR03646158X (SPR)s40430-018-1376-1-e DE-627 ger DE-627 rakwb eng Garcia, Raphael Rustici verfasserin aut Relevant factors for the energy consumption of industrial robots 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Brazilian Society of Mechanical Sciences and Engineering 2018 Abstract This work investigates the energy consumption of industrial robots in the context of automotive industry. The purpose is to identify the most influencing parameters and variables and to propose best practices with focus on energy efficiency. The analysis approach is composed of three experiments performed in a simulation environment that test different values of programming parameters and variables, such as joint speed, acceleration, robot payload. The first experiment focuses on energy consumption of robots at standstill. The second one considers the robot moving along different paths. Finally, the third one analyses how the joint friction is affected by load, speed and temperature and how it influences the energy consumption. Results show that at standstill, it is important to reduce dwell time, select an energy efficient position and reduce the programmed value of the timer responsible for turning off the servomotors. While moving, it is important to select maximum continuous termination for intermediate points and avoid low speeds. Regarding friction variation, results show that at high motor speed, low temperatures increase energy consumption. In order to evaluate the contribution of the best practices in a real environment, they are applied to a welding robotic cell of an automotive industry. Energy consumption (dpeaa)DE-He213 Industrial robots (dpeaa)DE-He213 Friction modelling (dpeaa)DE-He213 Automotive industry (dpeaa)DE-He213 Bittencourt, André Carvalho aut Villani, Emilia (orcid)0000-0002-6804-1453 aut Enthalten in Journal of the Brazilian Society of Mechanical Sciences and Engineering Berlin : Springer, 2003 40(2018), 9 vom: 03. Sept. (DE-627)387477950 (DE-600)2145288-X 1806-3691 nnns volume:40 year:2018 number:9 day:03 month:09 https://dx.doi.org/10.1007/s40430-018-1376-1 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_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_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 40 2018 9 03 09 |
allfields_unstemmed |
10.1007/s40430-018-1376-1 doi (DE-627)SPR03646158X (SPR)s40430-018-1376-1-e DE-627 ger DE-627 rakwb eng Garcia, Raphael Rustici verfasserin aut Relevant factors for the energy consumption of industrial robots 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Brazilian Society of Mechanical Sciences and Engineering 2018 Abstract This work investigates the energy consumption of industrial robots in the context of automotive industry. The purpose is to identify the most influencing parameters and variables and to propose best practices with focus on energy efficiency. The analysis approach is composed of three experiments performed in a simulation environment that test different values of programming parameters and variables, such as joint speed, acceleration, robot payload. The first experiment focuses on energy consumption of robots at standstill. The second one considers the robot moving along different paths. Finally, the third one analyses how the joint friction is affected by load, speed and temperature and how it influences the energy consumption. Results show that at standstill, it is important to reduce dwell time, select an energy efficient position and reduce the programmed value of the timer responsible for turning off the servomotors. While moving, it is important to select maximum continuous termination for intermediate points and avoid low speeds. Regarding friction variation, results show that at high motor speed, low temperatures increase energy consumption. In order to evaluate the contribution of the best practices in a real environment, they are applied to a welding robotic cell of an automotive industry. Energy consumption (dpeaa)DE-He213 Industrial robots (dpeaa)DE-He213 Friction modelling (dpeaa)DE-He213 Automotive industry (dpeaa)DE-He213 Bittencourt, André Carvalho aut Villani, Emilia (orcid)0000-0002-6804-1453 aut Enthalten in Journal of the Brazilian Society of Mechanical Sciences and Engineering Berlin : Springer, 2003 40(2018), 9 vom: 03. Sept. (DE-627)387477950 (DE-600)2145288-X 1806-3691 nnns volume:40 year:2018 number:9 day:03 month:09 https://dx.doi.org/10.1007/s40430-018-1376-1 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_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_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 40 2018 9 03 09 |
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10.1007/s40430-018-1376-1 doi (DE-627)SPR03646158X (SPR)s40430-018-1376-1-e DE-627 ger DE-627 rakwb eng Garcia, Raphael Rustici verfasserin aut Relevant factors for the energy consumption of industrial robots 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Brazilian Society of Mechanical Sciences and Engineering 2018 Abstract This work investigates the energy consumption of industrial robots in the context of automotive industry. The purpose is to identify the most influencing parameters and variables and to propose best practices with focus on energy efficiency. The analysis approach is composed of three experiments performed in a simulation environment that test different values of programming parameters and variables, such as joint speed, acceleration, robot payload. The first experiment focuses on energy consumption of robots at standstill. The second one considers the robot moving along different paths. Finally, the third one analyses how the joint friction is affected by load, speed and temperature and how it influences the energy consumption. Results show that at standstill, it is important to reduce dwell time, select an energy efficient position and reduce the programmed value of the timer responsible for turning off the servomotors. While moving, it is important to select maximum continuous termination for intermediate points and avoid low speeds. Regarding friction variation, results show that at high motor speed, low temperatures increase energy consumption. In order to evaluate the contribution of the best practices in a real environment, they are applied to a welding robotic cell of an automotive industry. Energy consumption (dpeaa)DE-He213 Industrial robots (dpeaa)DE-He213 Friction modelling (dpeaa)DE-He213 Automotive industry (dpeaa)DE-He213 Bittencourt, André Carvalho aut Villani, Emilia (orcid)0000-0002-6804-1453 aut Enthalten in Journal of the Brazilian Society of Mechanical Sciences and Engineering Berlin : Springer, 2003 40(2018), 9 vom: 03. Sept. (DE-627)387477950 (DE-600)2145288-X 1806-3691 nnns volume:40 year:2018 number:9 day:03 month:09 https://dx.doi.org/10.1007/s40430-018-1376-1 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_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_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 40 2018 9 03 09 |
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10.1007/s40430-018-1376-1 doi (DE-627)SPR03646158X (SPR)s40430-018-1376-1-e DE-627 ger DE-627 rakwb eng Garcia, Raphael Rustici verfasserin aut Relevant factors for the energy consumption of industrial robots 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Brazilian Society of Mechanical Sciences and Engineering 2018 Abstract This work investigates the energy consumption of industrial robots in the context of automotive industry. The purpose is to identify the most influencing parameters and variables and to propose best practices with focus on energy efficiency. The analysis approach is composed of three experiments performed in a simulation environment that test different values of programming parameters and variables, such as joint speed, acceleration, robot payload. The first experiment focuses on energy consumption of robots at standstill. The second one considers the robot moving along different paths. Finally, the third one analyses how the joint friction is affected by load, speed and temperature and how it influences the energy consumption. Results show that at standstill, it is important to reduce dwell time, select an energy efficient position and reduce the programmed value of the timer responsible for turning off the servomotors. While moving, it is important to select maximum continuous termination for intermediate points and avoid low speeds. Regarding friction variation, results show that at high motor speed, low temperatures increase energy consumption. In order to evaluate the contribution of the best practices in a real environment, they are applied to a welding robotic cell of an automotive industry. Energy consumption (dpeaa)DE-He213 Industrial robots (dpeaa)DE-He213 Friction modelling (dpeaa)DE-He213 Automotive industry (dpeaa)DE-He213 Bittencourt, André Carvalho aut Villani, Emilia (orcid)0000-0002-6804-1453 aut Enthalten in Journal of the Brazilian Society of Mechanical Sciences and Engineering Berlin : Springer, 2003 40(2018), 9 vom: 03. Sept. (DE-627)387477950 (DE-600)2145288-X 1806-3691 nnns volume:40 year:2018 number:9 day:03 month:09 https://dx.doi.org/10.1007/s40430-018-1376-1 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_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_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 40 2018 9 03 09 |
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Garcia, Raphael Rustici @@aut@@ Bittencourt, André Carvalho @@aut@@ Villani, Emilia @@aut@@ |
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Garcia, Raphael Rustici |
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Garcia, Raphael Rustici misc Energy consumption misc Industrial robots misc Friction modelling misc Automotive industry Relevant factors for the energy consumption of industrial robots |
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Relevant factors for the energy consumption of industrial robots Energy consumption (dpeaa)DE-He213 Industrial robots (dpeaa)DE-He213 Friction modelling (dpeaa)DE-He213 Automotive industry (dpeaa)DE-He213 |
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relevant factors for the energy consumption of industrial robots |
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Relevant factors for the energy consumption of industrial robots |
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Abstract This work investigates the energy consumption of industrial robots in the context of automotive industry. The purpose is to identify the most influencing parameters and variables and to propose best practices with focus on energy efficiency. The analysis approach is composed of three experiments performed in a simulation environment that test different values of programming parameters and variables, such as joint speed, acceleration, robot payload. The first experiment focuses on energy consumption of robots at standstill. The second one considers the robot moving along different paths. Finally, the third one analyses how the joint friction is affected by load, speed and temperature and how it influences the energy consumption. Results show that at standstill, it is important to reduce dwell time, select an energy efficient position and reduce the programmed value of the timer responsible for turning off the servomotors. While moving, it is important to select maximum continuous termination for intermediate points and avoid low speeds. Regarding friction variation, results show that at high motor speed, low temperatures increase energy consumption. In order to evaluate the contribution of the best practices in a real environment, they are applied to a welding robotic cell of an automotive industry. © The Brazilian Society of Mechanical Sciences and Engineering 2018 |
abstractGer |
Abstract This work investigates the energy consumption of industrial robots in the context of automotive industry. The purpose is to identify the most influencing parameters and variables and to propose best practices with focus on energy efficiency. The analysis approach is composed of three experiments performed in a simulation environment that test different values of programming parameters and variables, such as joint speed, acceleration, robot payload. The first experiment focuses on energy consumption of robots at standstill. The second one considers the robot moving along different paths. Finally, the third one analyses how the joint friction is affected by load, speed and temperature and how it influences the energy consumption. Results show that at standstill, it is important to reduce dwell time, select an energy efficient position and reduce the programmed value of the timer responsible for turning off the servomotors. While moving, it is important to select maximum continuous termination for intermediate points and avoid low speeds. Regarding friction variation, results show that at high motor speed, low temperatures increase energy consumption. In order to evaluate the contribution of the best practices in a real environment, they are applied to a welding robotic cell of an automotive industry. © The Brazilian Society of Mechanical Sciences and Engineering 2018 |
abstract_unstemmed |
Abstract This work investigates the energy consumption of industrial robots in the context of automotive industry. The purpose is to identify the most influencing parameters and variables and to propose best practices with focus on energy efficiency. The analysis approach is composed of three experiments performed in a simulation environment that test different values of programming parameters and variables, such as joint speed, acceleration, robot payload. The first experiment focuses on energy consumption of robots at standstill. The second one considers the robot moving along different paths. Finally, the third one analyses how the joint friction is affected by load, speed and temperature and how it influences the energy consumption. Results show that at standstill, it is important to reduce dwell time, select an energy efficient position and reduce the programmed value of the timer responsible for turning off the servomotors. While moving, it is important to select maximum continuous termination for intermediate points and avoid low speeds. Regarding friction variation, results show that at high motor speed, low temperatures increase energy consumption. In order to evaluate the contribution of the best practices in a real environment, they are applied to a welding robotic cell of an automotive industry. © The Brazilian Society of Mechanical Sciences and Engineering 2018 |
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Relevant factors for the energy consumption of industrial robots |
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The purpose is to identify the most influencing parameters and variables and to propose best practices with focus on energy efficiency. The analysis approach is composed of three experiments performed in a simulation environment that test different values of programming parameters and variables, such as joint speed, acceleration, robot payload. The first experiment focuses on energy consumption of robots at standstill. The second one considers the robot moving along different paths. Finally, the third one analyses how the joint friction is affected by load, speed and temperature and how it influences the energy consumption. Results show that at standstill, it is important to reduce dwell time, select an energy efficient position and reduce the programmed value of the timer responsible for turning off the servomotors. While moving, it is important to select maximum continuous termination for intermediate points and avoid low speeds. Regarding friction variation, results show that at high motor speed, low temperatures increase energy consumption. In order to evaluate the contribution of the best practices in a real environment, they are applied to a welding robotic cell of an automotive industry.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Energy consumption</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Industrial robots</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Friction modelling</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Automotive industry</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Bittencourt, André Carvalho</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Villani, Emilia</subfield><subfield code="0">(orcid)0000-0002-6804-1453</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of the Brazilian Society of Mechanical Sciences and Engineering</subfield><subfield code="d">Berlin : Springer, 2003</subfield><subfield code="g">40(2018), 9 vom: 03. 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