Production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future
Abstract Current concept, development, and testing applications in production concerning Cyber-Physical Systems (CPS), Industry 4.0 (I40), and Internet of Things (IoT) are mainly addressing fully autonomous systems, fostered by an increase in available technologies regarding distributed decision-mak...
Ausführliche Beschreibung
Autor*in: |
Klumpp, Matthias [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2019 |
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Schlagwörter: |
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Anmerkung: |
© The Author(s) 2019 |
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Übergeordnetes Werk: |
Enthalten in: The international journal of advanced manufacturing technology - London : Springer, 1985, 105(2019), 9 vom: 12. Mai, Seite 3691-3709 |
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Übergeordnetes Werk: |
volume:105 ; year:2019 ; number:9 ; day:12 ; month:05 ; pages:3691-3709 |
Links: |
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DOI / URN: |
10.1007/s00170-019-03785-0 |
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Katalog-ID: |
SPR001502794 |
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520 | |a Abstract Current concept, development, and testing applications in production concerning Cyber-Physical Systems (CPS), Industry 4.0 (I40), and Internet of Things (IoT) are mainly addressing fully autonomous systems, fostered by an increase in available technologies regarding distributed decision-making, sensors, and actuators for robotics systems. This is applied also to production logistics settings with a multitude of transport tasks, e.g., between warehousing or material supply stations and production locations within larger production sites as for example in the automotive industry. In most cases, mixed environments where automated systems and humans collaborate (e.g., cobots) are not in the center of analysis and development endeavors although the worker’s adoption and acceptance of new technologies are of crucial relevance. From an interdisciplinary research perspective, this constitutes an important research gap, as the future challenges for successful automated systems will rely mainly on human-computer interaction (HCI) in connection with an efficient collaboration between motivated workers, automated robotics, and transportation systems. We develop a HCI efficiency description in production logistics based on an interdisciplinary analysis consisting of three interdependent parts: (i) a production logistics literature review and process study, (ii) a computer science literature review and simulation study for an existing autonomous traffic control algorithm applicable to production logistics settings with the specific inclusion of human actors, and (iii) a work science analysis for automation settings referring to theoretical foundations and empirical findings regarding the management of workers in digital work settings. We conclude with practical implications and discuss avenues for future research and business applications. | ||
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650 | 4 | |a Autonomous traffic control |7 (dpeaa)DE-He213 | |
700 | 1 | |a Hesenius, Marc |4 aut | |
700 | 1 | |a Meyer, Ole |4 aut | |
700 | 1 | |a Ruiner, Caroline |4 aut | |
700 | 1 | |a Gruhn, Volker |4 aut | |
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10.1007/s00170-019-03785-0 doi (DE-627)SPR001502794 (SPR)s00170-019-03785-0-e DE-627 ger DE-627 rakwb eng Klumpp, Matthias verfasserin (orcid)0000-0002-7543-2751 aut Production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Abstract Current concept, development, and testing applications in production concerning Cyber-Physical Systems (CPS), Industry 4.0 (I40), and Internet of Things (IoT) are mainly addressing fully autonomous systems, fostered by an increase in available technologies regarding distributed decision-making, sensors, and actuators for robotics systems. This is applied also to production logistics settings with a multitude of transport tasks, e.g., between warehousing or material supply stations and production locations within larger production sites as for example in the automotive industry. In most cases, mixed environments where automated systems and humans collaborate (e.g., cobots) are not in the center of analysis and development endeavors although the worker’s adoption and acceptance of new technologies are of crucial relevance. From an interdisciplinary research perspective, this constitutes an important research gap, as the future challenges for successful automated systems will rely mainly on human-computer interaction (HCI) in connection with an efficient collaboration between motivated workers, automated robotics, and transportation systems. We develop a HCI efficiency description in production logistics based on an interdisciplinary analysis consisting of three interdependent parts: (i) a production logistics literature review and process study, (ii) a computer science literature review and simulation study for an existing autonomous traffic control algorithm applicable to production logistics settings with the specific inclusion of human actors, and (iii) a work science analysis for automation settings referring to theoretical foundations and empirical findings regarding the management of workers in digital work settings. We conclude with practical implications and discuss avenues for future research and business applications. Production logistics (dpeaa)DE-He213 HCI (dpeaa)DE-He213 Cobots (dpeaa)DE-He213 Autonomous traffic control (dpeaa)DE-He213 Hesenius, Marc aut Meyer, Ole aut Ruiner, Caroline aut Gruhn, Volker aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 105(2019), 9 vom: 12. Mai, Seite 3691-3709 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:105 year:2019 number:9 day:12 month:05 pages:3691-3709 https://dx.doi.org/10.1007/s00170-019-03785-0 kostenfrei 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 105 2019 9 12 05 3691-3709 |
spelling |
10.1007/s00170-019-03785-0 doi (DE-627)SPR001502794 (SPR)s00170-019-03785-0-e DE-627 ger DE-627 rakwb eng Klumpp, Matthias verfasserin (orcid)0000-0002-7543-2751 aut Production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Abstract Current concept, development, and testing applications in production concerning Cyber-Physical Systems (CPS), Industry 4.0 (I40), and Internet of Things (IoT) are mainly addressing fully autonomous systems, fostered by an increase in available technologies regarding distributed decision-making, sensors, and actuators for robotics systems. This is applied also to production logistics settings with a multitude of transport tasks, e.g., between warehousing or material supply stations and production locations within larger production sites as for example in the automotive industry. In most cases, mixed environments where automated systems and humans collaborate (e.g., cobots) are not in the center of analysis and development endeavors although the worker’s adoption and acceptance of new technologies are of crucial relevance. From an interdisciplinary research perspective, this constitutes an important research gap, as the future challenges for successful automated systems will rely mainly on human-computer interaction (HCI) in connection with an efficient collaboration between motivated workers, automated robotics, and transportation systems. We develop a HCI efficiency description in production logistics based on an interdisciplinary analysis consisting of three interdependent parts: (i) a production logistics literature review and process study, (ii) a computer science literature review and simulation study for an existing autonomous traffic control algorithm applicable to production logistics settings with the specific inclusion of human actors, and (iii) a work science analysis for automation settings referring to theoretical foundations and empirical findings regarding the management of workers in digital work settings. We conclude with practical implications and discuss avenues for future research and business applications. Production logistics (dpeaa)DE-He213 HCI (dpeaa)DE-He213 Cobots (dpeaa)DE-He213 Autonomous traffic control (dpeaa)DE-He213 Hesenius, Marc aut Meyer, Ole aut Ruiner, Caroline aut Gruhn, Volker aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 105(2019), 9 vom: 12. Mai, Seite 3691-3709 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:105 year:2019 number:9 day:12 month:05 pages:3691-3709 https://dx.doi.org/10.1007/s00170-019-03785-0 kostenfrei 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 105 2019 9 12 05 3691-3709 |
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10.1007/s00170-019-03785-0 doi (DE-627)SPR001502794 (SPR)s00170-019-03785-0-e DE-627 ger DE-627 rakwb eng Klumpp, Matthias verfasserin (orcid)0000-0002-7543-2751 aut Production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Abstract Current concept, development, and testing applications in production concerning Cyber-Physical Systems (CPS), Industry 4.0 (I40), and Internet of Things (IoT) are mainly addressing fully autonomous systems, fostered by an increase in available technologies regarding distributed decision-making, sensors, and actuators for robotics systems. This is applied also to production logistics settings with a multitude of transport tasks, e.g., between warehousing or material supply stations and production locations within larger production sites as for example in the automotive industry. In most cases, mixed environments where automated systems and humans collaborate (e.g., cobots) are not in the center of analysis and development endeavors although the worker’s adoption and acceptance of new technologies are of crucial relevance. From an interdisciplinary research perspective, this constitutes an important research gap, as the future challenges for successful automated systems will rely mainly on human-computer interaction (HCI) in connection with an efficient collaboration between motivated workers, automated robotics, and transportation systems. We develop a HCI efficiency description in production logistics based on an interdisciplinary analysis consisting of three interdependent parts: (i) a production logistics literature review and process study, (ii) a computer science literature review and simulation study for an existing autonomous traffic control algorithm applicable to production logistics settings with the specific inclusion of human actors, and (iii) a work science analysis for automation settings referring to theoretical foundations and empirical findings regarding the management of workers in digital work settings. We conclude with practical implications and discuss avenues for future research and business applications. Production logistics (dpeaa)DE-He213 HCI (dpeaa)DE-He213 Cobots (dpeaa)DE-He213 Autonomous traffic control (dpeaa)DE-He213 Hesenius, Marc aut Meyer, Ole aut Ruiner, Caroline aut Gruhn, Volker aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 105(2019), 9 vom: 12. Mai, Seite 3691-3709 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:105 year:2019 number:9 day:12 month:05 pages:3691-3709 https://dx.doi.org/10.1007/s00170-019-03785-0 kostenfrei 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 105 2019 9 12 05 3691-3709 |
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10.1007/s00170-019-03785-0 doi (DE-627)SPR001502794 (SPR)s00170-019-03785-0-e DE-627 ger DE-627 rakwb eng Klumpp, Matthias verfasserin (orcid)0000-0002-7543-2751 aut Production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Abstract Current concept, development, and testing applications in production concerning Cyber-Physical Systems (CPS), Industry 4.0 (I40), and Internet of Things (IoT) are mainly addressing fully autonomous systems, fostered by an increase in available technologies regarding distributed decision-making, sensors, and actuators for robotics systems. This is applied also to production logistics settings with a multitude of transport tasks, e.g., between warehousing or material supply stations and production locations within larger production sites as for example in the automotive industry. In most cases, mixed environments where automated systems and humans collaborate (e.g., cobots) are not in the center of analysis and development endeavors although the worker’s adoption and acceptance of new technologies are of crucial relevance. From an interdisciplinary research perspective, this constitutes an important research gap, as the future challenges for successful automated systems will rely mainly on human-computer interaction (HCI) in connection with an efficient collaboration between motivated workers, automated robotics, and transportation systems. We develop a HCI efficiency description in production logistics based on an interdisciplinary analysis consisting of three interdependent parts: (i) a production logistics literature review and process study, (ii) a computer science literature review and simulation study for an existing autonomous traffic control algorithm applicable to production logistics settings with the specific inclusion of human actors, and (iii) a work science analysis for automation settings referring to theoretical foundations and empirical findings regarding the management of workers in digital work settings. We conclude with practical implications and discuss avenues for future research and business applications. Production logistics (dpeaa)DE-He213 HCI (dpeaa)DE-He213 Cobots (dpeaa)DE-He213 Autonomous traffic control (dpeaa)DE-He213 Hesenius, Marc aut Meyer, Ole aut Ruiner, Caroline aut Gruhn, Volker aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 105(2019), 9 vom: 12. Mai, Seite 3691-3709 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:105 year:2019 number:9 day:12 month:05 pages:3691-3709 https://dx.doi.org/10.1007/s00170-019-03785-0 kostenfrei 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 105 2019 9 12 05 3691-3709 |
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10.1007/s00170-019-03785-0 doi (DE-627)SPR001502794 (SPR)s00170-019-03785-0-e DE-627 ger DE-627 rakwb eng Klumpp, Matthias verfasserin (orcid)0000-0002-7543-2751 aut Production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Abstract Current concept, development, and testing applications in production concerning Cyber-Physical Systems (CPS), Industry 4.0 (I40), and Internet of Things (IoT) are mainly addressing fully autonomous systems, fostered by an increase in available technologies regarding distributed decision-making, sensors, and actuators for robotics systems. This is applied also to production logistics settings with a multitude of transport tasks, e.g., between warehousing or material supply stations and production locations within larger production sites as for example in the automotive industry. In most cases, mixed environments where automated systems and humans collaborate (e.g., cobots) are not in the center of analysis and development endeavors although the worker’s adoption and acceptance of new technologies are of crucial relevance. From an interdisciplinary research perspective, this constitutes an important research gap, as the future challenges for successful automated systems will rely mainly on human-computer interaction (HCI) in connection with an efficient collaboration between motivated workers, automated robotics, and transportation systems. We develop a HCI efficiency description in production logistics based on an interdisciplinary analysis consisting of three interdependent parts: (i) a production logistics literature review and process study, (ii) a computer science literature review and simulation study for an existing autonomous traffic control algorithm applicable to production logistics settings with the specific inclusion of human actors, and (iii) a work science analysis for automation settings referring to theoretical foundations and empirical findings regarding the management of workers in digital work settings. We conclude with practical implications and discuss avenues for future research and business applications. Production logistics (dpeaa)DE-He213 HCI (dpeaa)DE-He213 Cobots (dpeaa)DE-He213 Autonomous traffic control (dpeaa)DE-He213 Hesenius, Marc aut Meyer, Ole aut Ruiner, Caroline aut Gruhn, Volker aut Enthalten in The international journal of advanced manufacturing technology London : Springer, 1985 105(2019), 9 vom: 12. Mai, Seite 3691-3709 (DE-627)270127712 (DE-600)1476510-X 1433-3015 nnns volume:105 year:2019 number:9 day:12 month:05 pages:3691-3709 https://dx.doi.org/10.1007/s00170-019-03785-0 kostenfrei 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 105 2019 9 12 05 3691-3709 |
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Enthalten in The international journal of advanced manufacturing technology 105(2019), 9 vom: 12. Mai, Seite 3691-3709 volume:105 year:2019 number:9 day:12 month:05 pages:3691-3709 |
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Klumpp, Matthias @@aut@@ Hesenius, Marc @@aut@@ Meyer, Ole @@aut@@ Ruiner, Caroline @@aut@@ Gruhn, Volker @@aut@@ |
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Klumpp, Matthias |
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Klumpp, Matthias misc Production logistics misc HCI misc Cobots misc Autonomous traffic control Production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future |
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Production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future Production logistics (dpeaa)DE-He213 HCI (dpeaa)DE-He213 Cobots (dpeaa)DE-He213 Autonomous traffic control (dpeaa)DE-He213 |
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Production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future |
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production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future |
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Production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future |
abstract |
Abstract Current concept, development, and testing applications in production concerning Cyber-Physical Systems (CPS), Industry 4.0 (I40), and Internet of Things (IoT) are mainly addressing fully autonomous systems, fostered by an increase in available technologies regarding distributed decision-making, sensors, and actuators for robotics systems. This is applied also to production logistics settings with a multitude of transport tasks, e.g., between warehousing or material supply stations and production locations within larger production sites as for example in the automotive industry. In most cases, mixed environments where automated systems and humans collaborate (e.g., cobots) are not in the center of analysis and development endeavors although the worker’s adoption and acceptance of new technologies are of crucial relevance. From an interdisciplinary research perspective, this constitutes an important research gap, as the future challenges for successful automated systems will rely mainly on human-computer interaction (HCI) in connection with an efficient collaboration between motivated workers, automated robotics, and transportation systems. We develop a HCI efficiency description in production logistics based on an interdisciplinary analysis consisting of three interdependent parts: (i) a production logistics literature review and process study, (ii) a computer science literature review and simulation study for an existing autonomous traffic control algorithm applicable to production logistics settings with the specific inclusion of human actors, and (iii) a work science analysis for automation settings referring to theoretical foundations and empirical findings regarding the management of workers in digital work settings. We conclude with practical implications and discuss avenues for future research and business applications. © The Author(s) 2019 |
abstractGer |
Abstract Current concept, development, and testing applications in production concerning Cyber-Physical Systems (CPS), Industry 4.0 (I40), and Internet of Things (IoT) are mainly addressing fully autonomous systems, fostered by an increase in available technologies regarding distributed decision-making, sensors, and actuators for robotics systems. This is applied also to production logistics settings with a multitude of transport tasks, e.g., between warehousing or material supply stations and production locations within larger production sites as for example in the automotive industry. In most cases, mixed environments where automated systems and humans collaborate (e.g., cobots) are not in the center of analysis and development endeavors although the worker’s adoption and acceptance of new technologies are of crucial relevance. From an interdisciplinary research perspective, this constitutes an important research gap, as the future challenges for successful automated systems will rely mainly on human-computer interaction (HCI) in connection with an efficient collaboration between motivated workers, automated robotics, and transportation systems. We develop a HCI efficiency description in production logistics based on an interdisciplinary analysis consisting of three interdependent parts: (i) a production logistics literature review and process study, (ii) a computer science literature review and simulation study for an existing autonomous traffic control algorithm applicable to production logistics settings with the specific inclusion of human actors, and (iii) a work science analysis for automation settings referring to theoretical foundations and empirical findings regarding the management of workers in digital work settings. We conclude with practical implications and discuss avenues for future research and business applications. © The Author(s) 2019 |
abstract_unstemmed |
Abstract Current concept, development, and testing applications in production concerning Cyber-Physical Systems (CPS), Industry 4.0 (I40), and Internet of Things (IoT) are mainly addressing fully autonomous systems, fostered by an increase in available technologies regarding distributed decision-making, sensors, and actuators for robotics systems. This is applied also to production logistics settings with a multitude of transport tasks, e.g., between warehousing or material supply stations and production locations within larger production sites as for example in the automotive industry. In most cases, mixed environments where automated systems and humans collaborate (e.g., cobots) are not in the center of analysis and development endeavors although the worker’s adoption and acceptance of new technologies are of crucial relevance. From an interdisciplinary research perspective, this constitutes an important research gap, as the future challenges for successful automated systems will rely mainly on human-computer interaction (HCI) in connection with an efficient collaboration between motivated workers, automated robotics, and transportation systems. We develop a HCI efficiency description in production logistics based on an interdisciplinary analysis consisting of three interdependent parts: (i) a production logistics literature review and process study, (ii) a computer science literature review and simulation study for an existing autonomous traffic control algorithm applicable to production logistics settings with the specific inclusion of human actors, and (iii) a work science analysis for automation settings referring to theoretical foundations and empirical findings regarding the management of workers in digital work settings. We conclude with practical implications and discuss avenues for future research and business applications. © The Author(s) 2019 |
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container_issue |
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title_short |
Production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future |
url |
https://dx.doi.org/10.1007/s00170-019-03785-0 |
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author2 |
Hesenius, Marc Meyer, Ole Ruiner, Caroline Gruhn, Volker |
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Hesenius, Marc Meyer, Ole Ruiner, Caroline Gruhn, Volker |
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doi_str |
10.1007/s00170-019-03785-0 |
up_date |
2024-07-03T22:59:49.119Z |
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score |
7.3992853 |