Adopting extended reality? A systematic review of manufacturing training and teaching applications

The training of future experts and operators in manufacturing engineering relies on understanding procedural processes that require applied practice. Yet, current manufacturing education and training overwhelmingly continues to depend on traditional pedagogical methods that segregate theoretical stu...
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Gespeichert in:

Autor*in:	de Giorgio, Andrea [verfasserIn] Monetti, Fabio Marco [verfasserIn] Maffei, Antonio [verfasserIn] Romero, Mario [verfasserIn] Wang, Lihui [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Extended reality Augmented reality Virtual reality Manufacturing Education Technology readiness level

Übergeordnetes Werk:	Enthalten in: Journal of manufacturing processes - Dearborn, Mich. : Soc., 1999, 71, Seite 645-663
Übergeordnetes Werk:	volume:71 ; pages:645-663

DOI / URN:	10.1016/j.jmsy.2023.10.016

Katalog-ID:	ELV065601475

Internformat


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520			\|a The training of future experts and operators in manufacturing engineering relies on understanding procedural processes that require applied practice. Yet, current manufacturing education and training overwhelmingly continues to depend on traditional pedagogical methods that segregate theoretical studies and practical training. While educational institutes have generally improved theoretical studies, they often lack facilities and labs to properly reproduce the working environments necessary for practice. Even in industrial settings, it is difficult, if not impossible, to halt the actual production lines to train new operators. Recently, applications with extended reality (XR) technologies, such as virtual, augmented, or mixed reality, reached a mature technology readiness level. With this technological advancement, we can envision a transition to a new teaching paradigm that exploits simulated learning environments. Thus, it becomes possible to bridge the gap between theory and practice for both students and industrial trainees. This article presents a systematic literature review of the main applications of XR technologies in manufacturing education, their goals and technology readiness levels, and a comprehensive overview of the development tools and experimental strategies deployed. This review contributes: (1) a state-of-the-art description of current research in XR education for manufacturing systems, and (2) a comprehensive analysis of the technological platforms, the experimental procedures and the analytical methodologies deployed in the body of literature examined. It serves as a guide for setting up and executing experimental designs for evaluating interventions of XR in manufacturing education and training.
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publishDate	2023
allfields	10.1016/j.jmsy.2023.10.016 doi (DE-627)ELV065601475 (ELSEVIER)S0278-6125(23)00217-0 DE-627 ger DE-627 rda eng 650 620 004 VZ de Giorgio, Andrea verfasserin (orcid)0000-0001-6064-5634 aut Adopting extended reality? A systematic review of manufacturing training and teaching applications 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The training of future experts and operators in manufacturing engineering relies on understanding procedural processes that require applied practice. Yet, current manufacturing education and training overwhelmingly continues to depend on traditional pedagogical methods that segregate theoretical studies and practical training. While educational institutes have generally improved theoretical studies, they often lack facilities and labs to properly reproduce the working environments necessary for practice. Even in industrial settings, it is difficult, if not impossible, to halt the actual production lines to train new operators. Recently, applications with extended reality (XR) technologies, such as virtual, augmented, or mixed reality, reached a mature technology readiness level. With this technological advancement, we can envision a transition to a new teaching paradigm that exploits simulated learning environments. Thus, it becomes possible to bridge the gap between theory and practice for both students and industrial trainees. This article presents a systematic literature review of the main applications of XR technologies in manufacturing education, their goals and technology readiness levels, and a comprehensive overview of the development tools and experimental strategies deployed. This review contributes: (1) a state-of-the-art description of current research in XR education for manufacturing systems, and (2) a comprehensive analysis of the technological platforms, the experimental procedures and the analytical methodologies deployed in the body of literature examined. It serves as a guide for setting up and executing experimental designs for evaluating interventions of XR in manufacturing education and training. Extended reality Augmented reality Virtual reality Manufacturing Education Technology readiness level Monetti, Fabio Marco verfasserin (orcid)0000-0003-2993-511X aut Maffei, Antonio verfasserin (orcid)0000-0002-0723-1712 aut Romero, Mario verfasserin (orcid)0000-0003-4616-189X aut Wang, Lihui verfasserin (orcid)0000-0001-8679-8049 aut Enthalten in Journal of manufacturing processes Dearborn, Mich. : Soc., 1999 71, Seite 645-663 Online-Ressource (DE-627)472650998 (DE-600)2168529-0 (DE-576)302969888 nnns volume:71 pages:645-663 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 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_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4338 GBV_ILN_4393 GBV_ILN_4700 AR 71 645-663
spelling	10.1016/j.jmsy.2023.10.016 doi (DE-627)ELV065601475 (ELSEVIER)S0278-6125(23)00217-0 DE-627 ger DE-627 rda eng 650 620 004 VZ de Giorgio, Andrea verfasserin (orcid)0000-0001-6064-5634 aut Adopting extended reality? A systematic review of manufacturing training and teaching applications 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The training of future experts and operators in manufacturing engineering relies on understanding procedural processes that require applied practice. Yet, current manufacturing education and training overwhelmingly continues to depend on traditional pedagogical methods that segregate theoretical studies and practical training. While educational institutes have generally improved theoretical studies, they often lack facilities and labs to properly reproduce the working environments necessary for practice. Even in industrial settings, it is difficult, if not impossible, to halt the actual production lines to train new operators. Recently, applications with extended reality (XR) technologies, such as virtual, augmented, or mixed reality, reached a mature technology readiness level. With this technological advancement, we can envision a transition to a new teaching paradigm that exploits simulated learning environments. Thus, it becomes possible to bridge the gap between theory and practice for both students and industrial trainees. This article presents a systematic literature review of the main applications of XR technologies in manufacturing education, their goals and technology readiness levels, and a comprehensive overview of the development tools and experimental strategies deployed. This review contributes: (1) a state-of-the-art description of current research in XR education for manufacturing systems, and (2) a comprehensive analysis of the technological platforms, the experimental procedures and the analytical methodologies deployed in the body of literature examined. It serves as a guide for setting up and executing experimental designs for evaluating interventions of XR in manufacturing education and training. Extended reality Augmented reality Virtual reality Manufacturing Education Technology readiness level Monetti, Fabio Marco verfasserin (orcid)0000-0003-2993-511X aut Maffei, Antonio verfasserin (orcid)0000-0002-0723-1712 aut Romero, Mario verfasserin (orcid)0000-0003-4616-189X aut Wang, Lihui verfasserin (orcid)0000-0001-8679-8049 aut Enthalten in Journal of manufacturing processes Dearborn, Mich. : Soc., 1999 71, Seite 645-663 Online-Ressource (DE-627)472650998 (DE-600)2168529-0 (DE-576)302969888 nnns volume:71 pages:645-663 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 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_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4338 GBV_ILN_4393 GBV_ILN_4700 AR 71 645-663
allfields_unstemmed	10.1016/j.jmsy.2023.10.016 doi (DE-627)ELV065601475 (ELSEVIER)S0278-6125(23)00217-0 DE-627 ger DE-627 rda eng 650 620 004 VZ de Giorgio, Andrea verfasserin (orcid)0000-0001-6064-5634 aut Adopting extended reality? A systematic review of manufacturing training and teaching applications 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The training of future experts and operators in manufacturing engineering relies on understanding procedural processes that require applied practice. Yet, current manufacturing education and training overwhelmingly continues to depend on traditional pedagogical methods that segregate theoretical studies and practical training. While educational institutes have generally improved theoretical studies, they often lack facilities and labs to properly reproduce the working environments necessary for practice. Even in industrial settings, it is difficult, if not impossible, to halt the actual production lines to train new operators. Recently, applications with extended reality (XR) technologies, such as virtual, augmented, or mixed reality, reached a mature technology readiness level. With this technological advancement, we can envision a transition to a new teaching paradigm that exploits simulated learning environments. Thus, it becomes possible to bridge the gap between theory and practice for both students and industrial trainees. This article presents a systematic literature review of the main applications of XR technologies in manufacturing education, their goals and technology readiness levels, and a comprehensive overview of the development tools and experimental strategies deployed. This review contributes: (1) a state-of-the-art description of current research in XR education for manufacturing systems, and (2) a comprehensive analysis of the technological platforms, the experimental procedures and the analytical methodologies deployed in the body of literature examined. It serves as a guide for setting up and executing experimental designs for evaluating interventions of XR in manufacturing education and training. Extended reality Augmented reality Virtual reality Manufacturing Education Technology readiness level Monetti, Fabio Marco verfasserin (orcid)0000-0003-2993-511X aut Maffei, Antonio verfasserin (orcid)0000-0002-0723-1712 aut Romero, Mario verfasserin (orcid)0000-0003-4616-189X aut Wang, Lihui verfasserin (orcid)0000-0001-8679-8049 aut Enthalten in Journal of manufacturing processes Dearborn, Mich. : Soc., 1999 71, Seite 645-663 Online-Ressource (DE-627)472650998 (DE-600)2168529-0 (DE-576)302969888 nnns volume:71 pages:645-663 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 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_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4338 GBV_ILN_4393 GBV_ILN_4700 AR 71 645-663
allfieldsGer	10.1016/j.jmsy.2023.10.016 doi (DE-627)ELV065601475 (ELSEVIER)S0278-6125(23)00217-0 DE-627 ger DE-627 rda eng 650 620 004 VZ de Giorgio, Andrea verfasserin (orcid)0000-0001-6064-5634 aut Adopting extended reality? A systematic review of manufacturing training and teaching applications 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The training of future experts and operators in manufacturing engineering relies on understanding procedural processes that require applied practice. Yet, current manufacturing education and training overwhelmingly continues to depend on traditional pedagogical methods that segregate theoretical studies and practical training. While educational institutes have generally improved theoretical studies, they often lack facilities and labs to properly reproduce the working environments necessary for practice. Even in industrial settings, it is difficult, if not impossible, to halt the actual production lines to train new operators. Recently, applications with extended reality (XR) technologies, such as virtual, augmented, or mixed reality, reached a mature technology readiness level. With this technological advancement, we can envision a transition to a new teaching paradigm that exploits simulated learning environments. Thus, it becomes possible to bridge the gap between theory and practice for both students and industrial trainees. This article presents a systematic literature review of the main applications of XR technologies in manufacturing education, their goals and technology readiness levels, and a comprehensive overview of the development tools and experimental strategies deployed. This review contributes: (1) a state-of-the-art description of current research in XR education for manufacturing systems, and (2) a comprehensive analysis of the technological platforms, the experimental procedures and the analytical methodologies deployed in the body of literature examined. It serves as a guide for setting up and executing experimental designs for evaluating interventions of XR in manufacturing education and training. Extended reality Augmented reality Virtual reality Manufacturing Education Technology readiness level Monetti, Fabio Marco verfasserin (orcid)0000-0003-2993-511X aut Maffei, Antonio verfasserin (orcid)0000-0002-0723-1712 aut Romero, Mario verfasserin (orcid)0000-0003-4616-189X aut Wang, Lihui verfasserin (orcid)0000-0001-8679-8049 aut Enthalten in Journal of manufacturing processes Dearborn, Mich. : Soc., 1999 71, Seite 645-663 Online-Ressource (DE-627)472650998 (DE-600)2168529-0 (DE-576)302969888 nnns volume:71 pages:645-663 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 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_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4338 GBV_ILN_4393 GBV_ILN_4700 AR 71 645-663
allfieldsSound	10.1016/j.jmsy.2023.10.016 doi (DE-627)ELV065601475 (ELSEVIER)S0278-6125(23)00217-0 DE-627 ger DE-627 rda eng 650 620 004 VZ de Giorgio, Andrea verfasserin (orcid)0000-0001-6064-5634 aut Adopting extended reality? A systematic review of manufacturing training and teaching applications 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The training of future experts and operators in manufacturing engineering relies on understanding procedural processes that require applied practice. Yet, current manufacturing education and training overwhelmingly continues to depend on traditional pedagogical methods that segregate theoretical studies and practical training. While educational institutes have generally improved theoretical studies, they often lack facilities and labs to properly reproduce the working environments necessary for practice. Even in industrial settings, it is difficult, if not impossible, to halt the actual production lines to train new operators. Recently, applications with extended reality (XR) technologies, such as virtual, augmented, or mixed reality, reached a mature technology readiness level. With this technological advancement, we can envision a transition to a new teaching paradigm that exploits simulated learning environments. Thus, it becomes possible to bridge the gap between theory and practice for both students and industrial trainees. This article presents a systematic literature review of the main applications of XR technologies in manufacturing education, their goals and technology readiness levels, and a comprehensive overview of the development tools and experimental strategies deployed. This review contributes: (1) a state-of-the-art description of current research in XR education for manufacturing systems, and (2) a comprehensive analysis of the technological platforms, the experimental procedures and the analytical methodologies deployed in the body of literature examined. It serves as a guide for setting up and executing experimental designs for evaluating interventions of XR in manufacturing education and training. Extended reality Augmented reality Virtual reality Manufacturing Education Technology readiness level Monetti, Fabio Marco verfasserin (orcid)0000-0003-2993-511X aut Maffei, Antonio verfasserin (orcid)0000-0002-0723-1712 aut Romero, Mario verfasserin (orcid)0000-0003-4616-189X aut Wang, Lihui verfasserin (orcid)0000-0001-8679-8049 aut Enthalten in Journal of manufacturing processes Dearborn, Mich. : Soc., 1999 71, Seite 645-663 Online-Ressource (DE-627)472650998 (DE-600)2168529-0 (DE-576)302969888 nnns volume:71 pages:645-663 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 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_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4338 GBV_ILN_4393 GBV_ILN_4700 AR 71 645-663
language	English
source	Enthalten in Journal of manufacturing processes 71, Seite 645-663 volume:71 pages:645-663
sourceStr	Enthalten in Journal of manufacturing processes 71, Seite 645-663 volume:71 pages:645-663
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Extended reality Augmented reality Virtual reality Manufacturing Education Technology readiness level
dewey-raw	650
isfreeaccess_bool	false
container_title	Journal of manufacturing processes
authorswithroles_txt_mv	de Giorgio, Andrea @@aut@@ Monetti, Fabio Marco @@aut@@ Maffei, Antonio @@aut@@ Romero, Mario @@aut@@ Wang, Lihui @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	472650998
dewey-sort	3650
id	ELV065601475
language_de	englisch
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author	de Giorgio, Andrea
spellingShingle	de Giorgio, Andrea ddc 650 misc Extended reality misc Augmented reality misc Virtual reality misc Manufacturing misc Education misc Technology readiness level Adopting extended reality? A systematic review of manufacturing training and teaching applications
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title	Adopting extended reality? A systematic review of manufacturing training and teaching applications
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title_sort	adopting extended reality? a systematic review of manufacturing training and teaching applications
title_auth	Adopting extended reality? A systematic review of manufacturing training and teaching applications
abstract	The training of future experts and operators in manufacturing engineering relies on understanding procedural processes that require applied practice. Yet, current manufacturing education and training overwhelmingly continues to depend on traditional pedagogical methods that segregate theoretical studies and practical training. While educational institutes have generally improved theoretical studies, they often lack facilities and labs to properly reproduce the working environments necessary for practice. Even in industrial settings, it is difficult, if not impossible, to halt the actual production lines to train new operators. Recently, applications with extended reality (XR) technologies, such as virtual, augmented, or mixed reality, reached a mature technology readiness level. With this technological advancement, we can envision a transition to a new teaching paradigm that exploits simulated learning environments. Thus, it becomes possible to bridge the gap between theory and practice for both students and industrial trainees. This article presents a systematic literature review of the main applications of XR technologies in manufacturing education, their goals and technology readiness levels, and a comprehensive overview of the development tools and experimental strategies deployed. This review contributes: (1) a state-of-the-art description of current research in XR education for manufacturing systems, and (2) a comprehensive analysis of the technological platforms, the experimental procedures and the analytical methodologies deployed in the body of literature examined. It serves as a guide for setting up and executing experimental designs for evaluating interventions of XR in manufacturing education and training.
abstractGer	The training of future experts and operators in manufacturing engineering relies on understanding procedural processes that require applied practice. Yet, current manufacturing education and training overwhelmingly continues to depend on traditional pedagogical methods that segregate theoretical studies and practical training. While educational institutes have generally improved theoretical studies, they often lack facilities and labs to properly reproduce the working environments necessary for practice. Even in industrial settings, it is difficult, if not impossible, to halt the actual production lines to train new operators. Recently, applications with extended reality (XR) technologies, such as virtual, augmented, or mixed reality, reached a mature technology readiness level. With this technological advancement, we can envision a transition to a new teaching paradigm that exploits simulated learning environments. Thus, it becomes possible to bridge the gap between theory and practice for both students and industrial trainees. This article presents a systematic literature review of the main applications of XR technologies in manufacturing education, their goals and technology readiness levels, and a comprehensive overview of the development tools and experimental strategies deployed. This review contributes: (1) a state-of-the-art description of current research in XR education for manufacturing systems, and (2) a comprehensive analysis of the technological platforms, the experimental procedures and the analytical methodologies deployed in the body of literature examined. It serves as a guide for setting up and executing experimental designs for evaluating interventions of XR in manufacturing education and training.
abstract_unstemmed	The training of future experts and operators in manufacturing engineering relies on understanding procedural processes that require applied practice. Yet, current manufacturing education and training overwhelmingly continues to depend on traditional pedagogical methods that segregate theoretical studies and practical training. While educational institutes have generally improved theoretical studies, they often lack facilities and labs to properly reproduce the working environments necessary for practice. Even in industrial settings, it is difficult, if not impossible, to halt the actual production lines to train new operators. Recently, applications with extended reality (XR) technologies, such as virtual, augmented, or mixed reality, reached a mature technology readiness level. With this technological advancement, we can envision a transition to a new teaching paradigm that exploits simulated learning environments. Thus, it becomes possible to bridge the gap between theory and practice for both students and industrial trainees. This article presents a systematic literature review of the main applications of XR technologies in manufacturing education, their goals and technology readiness levels, and a comprehensive overview of the development tools and experimental strategies deployed. This review contributes: (1) a state-of-the-art description of current research in XR education for manufacturing systems, and (2) a comprehensive analysis of the technological platforms, the experimental procedures and the analytical methodologies deployed in the body of literature examined. It serves as a guide for setting up and executing experimental designs for evaluating interventions of XR in manufacturing education and training.
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title_short	Adopting extended reality? A systematic review of manufacturing training and teaching applications
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