The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Augmented reality in support of Industry 4.0—Implementation challenges and success factors
Open accessAbstract
Industrial augmented reality (AR) is an integral part of Industry 4.0 concepts, as it enables workers to access digital information and overlay that information with the physical world. While not being broadly adopted in some applications, the compound annual growth rate of the industrial AR market is projected to grow rapidly. Hence, it is important to understand the issues arising from implementation of AR in industry. This study identifies critical success factors and challenges for industrial AR implementation projects, based on an industry survey. The broadly used technology, organisation, environment (TOE) framework is used as a theoretical basis for the quantitative part of the questionnaire. A complementary qualitative part is used to underpin and extend the findings. It is found that, while technological aspects are of importance, organisational issues are more relevant for industry, which has not been reflected to the same extent in literature.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
Technology acceptance model: a literature review from 1986 to 2013
Marangunić, N., & Granić, A. (2015) · Universal Access in the Information Society · doi:10.1007/s10209-014-0348-1 · Cited by 2,458
Discriminant validity testing in marketing: an analysis, causes for concern, and proposed remedies
Voorhees, C. M., Brady, M. K., Calantone, R., & Ramirez, E. (2016) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-015-0455-4 · Cited by 2,111
Zhu, K., Kraemer, K. L., & Xu, S. (2006) · Management Science · doi:10.1287/mnsc.1050.0487 · Cited by 1,440
The Technology–Organization–Environment Framework
Baker, J. (2012) · Integrated Series in Information Systems · doi:10.1007/978-1-4419-6108-2_12 · Cited by 1,275
Understanding the determinants of RFID adoption in the manufacturing industry
Wang, Y.-M., Wang, Y.-S., & Yang, Y.-F. (2010) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2010.03.006 · Cited by 912
Predicting SMEs' adoption of enterprise systems
Ramdani, B., Kawalek, P., & Lorenzo, O. (2009) · Journal of Enterprise Information Management · doi:10.1108/17410390910922796 · Cited by 582
Huang, T.-L., & Liao, S. (2015) · Electronic Commerce Research · doi:10.1007/s10660-014-9163-2 · Cited by 476
The assimilation of RFID technology by Chinese companies: A technology diffusion perspective
Wei, J., Lowry, P. B., & Seedorf, S. (2015) · Information & Management · doi:10.1016/j.im.2015.05.001 · Cited by 112
Research works printed but not linked: 63
- Funk, 2016, Interactive worker assistance Proceedings of the 2016, 934
- Saunders, 2009
- Nee, 2012, Augmented reality applications in design and manufacturing, CIRP Ann., 61, 657, 10.1016/j.cirp.2012.05.010 · DOI · Paper page
- Han, 2017, Line-based initialization method for mobile augmented reality in aircraft assembly, Vis. Comput., 33, 1185, 10.1007/s00371-016-1281-5 · DOI
- Reif, 2009, Pick-by-vision: augmented reality supported order picking, Vis. Comput., 25, 461, 10.1007/s00371-009-0348-y · DOI
- Hanson, 2017, Augmented reality as a means of conveying picking information in kit preparation for mixed-model assembly, Comput. Ind. Eng., 113, 570, 10.1016/j.cie.2017.09.048 · DOI
- Stoltz, 2017, Augmented Reality in warehouse operations: opportunities and barriers, IFAC-PapersOnLine, 50, 12979, 10.1016/j.ifacol.2017.08.1807 · DOI
- Antonelli, 2015, Enhancing the quality of manual spot welding through augmented reality assisted guidance, Procedia CIRP, 33, 556, 10.1016/j.procir.2015.06.076 · doi:10.1016/j.procir.2015.06.076
- Segovia, 2015, Augmented reality as a tool for production and quality monitoring, Procedia Comput. Sci., 75, 291, 10.1016/j.procs.2015.12.250 · DOI
- Martinetti, 2017, Shaping the future maintenance operations: reflections on the adoptions of augmented reality through problems and opportunities, Procedia CIRP, 59, 14, 10.1016/j.procir.2016.10.130 · doi:10.1016/j.procir.2016.10.130
- Masoni, 2017, Supporting remote maintenance in Industry 4.0 through augmented reality, Procedia Manuf., 11, 1296, 10.1016/j.promfg.2017.07.257 · DOI · Paper page
- Mourtzis, 2017, Augmented reality application to support remote maintenance as a service in the robotics industry, Procedia CIRP, 63, 46, 10.1016/j.procir.2017.03.154 · DOI · Paper page
- Palmarini, 2017, An innovative process to select Augmented Reality (AR) technology for maintenance, Procedia CIRP, 59, 23, 10.1016/j.procir.2016.10.001 · doi:10.1016/j.procir.2016.10.001
- Zhu, 2012, An authorable context-aware augmented reality system to assist the maintenance technicians, Int. J. Adv. Manuf. Technol., 45, 1699
- Soete, 2015, Towards mixed reality in SCADA applications, IFAC-PapersOnLine, 48, 2417, 10.1016/j.ifacol.2015.06.450 · doi:10.1016/j.ifacol.2015.06.450
- Masood, 2018, Future-proofing the through-life engineering service systems, Procedia Manuf., 16, 179, 10.1016/j.promfg.2018.10.162 · DOI
- Makris, 2016, Augmented reality system for operator support in human–robot collaborative assembly, CIRP Ann., 65, 61, 10.1016/j.cirp.2016.04.038 · DOI · Paper page
- Michalos, 2018, Seamless human robot collaborative assembly - an automotive case study, Mechatronics, 1
- Palmarini, 2018, A systematic review of augmented reality applications in maintenance, Robot. Comput. Integr. Manuf., 49, 215, 10.1016/j.rcim.2017.06.002 · DOI · Paper page
- Gattullo, 2019, Towards augmented reality manuals for industry 4.0: a methodology, Robot. Comput. Integr. Manuf., 56, 276, 10.1016/j.rcim.2018.10.001 · DOI · Paper page
- Yew, 2016, Towards a griddable distributed manufacturing system with augmented reality interfaces, Robot. Comput. Integr. Manuf., 39, 43, 10.1016/j.rcim.2015.12.002 · DOI
- Matsas, 2018, Prototyping proactive and adaptive techniques for human-robot collaboration in manufacturing using virtual reality, Robot. Comput. Integr. Manuf., 50, 168, 10.1016/j.rcim.2017.09.005 · DOI
- Wang, 2016, Real-virtual components interaction for assembly simulation and planning, Robot. Comput. Integr. Manuf., 41, 102, 10.1016/j.rcim.2016.03.005 · DOI
- Fang, 2012, Interactive robot trajectory planning and simulation using augmented reality, Robot. Comput. Integr. Manuf, 28, 227, 10.1016/j.rcim.2011.09.003 · DOI
- Chong, 2009, Robot programming using augmented reality: an interactive method for planning collision-free paths, Robot. Comput. Integr. Manuf., 25, 689, 10.1016/j.rcim.2008.05.002 · DOI
- Holm, 2017, Adaptive instructions to novice shop-floor operators using augmented reality, J. Ind. Prod. Eng., 34, 362
- Syberfeldt, 2016, Support systems on the industrial shop-floors of the future – operators’ perspective on augmented reality, Procedia CIRP, 44, 108, 10.1016/j.procir.2016.02.017 · doi:10.1016/j.procir.2016.02.017
- Wang, 2018, Mechanical assembly assistance using marker-less augmented reality system, Assembly Autom., 38, 77, 10.1108/AA-11-2016-152 · DOI
- M. Majewski, W. Kacalak, Human-machine speech-based interfaces with augmented reality and interactive systems for controlling mobile cranes interactive collaborative robotics (2016) 89–98. · doi:10.1007/978-3-319-43955-6_12
- Zhou, 2007, The role of 3-D sound in human reaction and performance in augmented reality environments, IEEE Trans. Syst. Man Cybern., 37, 262, 10.1109/TSMCA.2006.886376 · DOI
- Radkowski, 2012, Interactive hand gesture-based assembly for augmented reality applications, ACHI, 303
- Wang, 2016, Multi-modal augmented-reality assembly guidance based on bare-hand interface, Adv. Eng. Inf., 30, 406, 10.1016/j.aei.2016.05.004 · DOI · Paper page
- Hou, 2013, A study on the benefits of augmented reality in retaining working memory in assembly tasks: a focus on differences in gender, Autom. Constr., 32, 38, 10.1016/j.autcon.2012.12.007 · DOI
- Mourtzis, 2017, Cloud-based augmented reality remote maintenance through shop-floor monitoring: a product-service system approach, J. Manuf. Sci. Eng., 139, 1, 10.1115/1.4035721 · DOI
- Serván, 2012, Assembly work instruction deployment using augmented reality, Key Eng. Mater., 502, 25, 10.4028/www.scientific.net/KEM.502.25 · doi:10.4028/www.scientific.net/kem.502.25
- Porcelli, 2013, Technical and organizational issues about the introduction of augmented reality in maintenance and technical assistance services, IFAC Proc. Vol., 46, 257, 10.3182/20130522-3-BR-4036.00024 · DOI
- Gavish, 2013, Evaluating virtual reality and augmented reality training for industrial maintenance and assembly tasks, Interact. Learn. Environ., 23, 778, 10.1080/10494820.2013.815221 · DOI · Paper page
- Doshi, 2017, Use of projector based augmented reality to improve manual spot-welding precision and accuracy for automotive manufacturing, Int. J. Adv. Manuf. Technol., 89, 1279, 10.1007/s00170-016-9164-5 · DOI · Paper page
- Zhu, 2005, Post-adoption variations in usage and value of e-business by organizations: cross-country evidence from the retail industry, Inf. Syst. Res., 16, 61, 10.1287/isre.1050.0045 · DOI · Paper page
- Zhu, 2010, What leads to post-implementation success of ERP?: an empirical study of the Chinese retail industry, Int. J. Inf. Manage., 30, 265, 10.1016/j.ijinfomgt.2009.09.007 · DOI · Paper page
- Jia, 2017, Enterprise 2.0 post-adoption: extending the information system continuance model based on the technology-organization-environment framework, Comput. Hum. Behav., 67, 95, 10.1016/j.chb.2016.10.022 · DOI
- Lee, 2017, An exploratory study of radio frequency identification (RFID) adoption in the healthcare industry, Eur. J. Inf. Syst., 16, 712, 10.1057/palgrave.ejis.3000716 · DOI · Paper page
- Scupola, 2014, The adoption of internet commerce by SMEs in the south of Italy: an environmental, technological and organizational perspective, J. Global Inf. Technol. Manage., 6, 52
- Mishra, 2007, Antecedents and consequences of Internet use in procurement: an empirical investigation of U.S. manufacturing firms, Inf. Syst. Res., 18, 103, 10.1287/isre.1070.0115 · DOI · Paper page
- Abdollahzadehgan, 2013, The organizational ciritical success factors for adopting cloud computing in SMEs, JISRI, 67
- K.N. Kumar, S. Chandra, S. Bharati et al., Factors Influencing Adoption of Augmented Reality Technology for e-Commerce PACIS Proceedings 2016 1–9.
- Sun, 2016, Understanding the factors affecting the organizational adoption of big data, J. Comput. Inf. Syst., 58, 193
- Yeh, 2018, Critical success factors for adoption of 3D printing, Technol. Forecast.Soc. Change, 132, 209, 10.1016/j.techfore.2018.02.003 · DOI · Paper page
- Davis, 1989, User acceptance of computer technology: a comparison of two theoretical models, Manage. Sci., 35, 982, 10.1287/mnsc.35.8.982 · DOI · Paper page
- Oliveira, 2014, Assessing the determinants of cloud computing adoption: an analysis of the manufacturing and services sectors, Inf. Manage., 51, 497, 10.1016/j.im.2014.03.006 · DOI · Paper page
- Gangwar, 2015, Understanding determinants of cloud computing adoption using an integrated TAM-TOE model, J. Enterp. Inf. Manage., 28, 107, 10.1108/JEIM-08-2013-0065 · DOI · Paper page
- Gonçalves, 2016, Factors that influence the adoption and implementation of public digital accounting according to the evaluation by managers of brazilian companies, J. Inf. Syst. Technol. Manage., 13, 193
- Chwelos, 2001, Research report: empirical test of an EDI adoption model, Inf. Syst. Res., 12, 304, 10.1287/isre.12.3.304.9708 · DOI · Paper page
- Zhu, 2004, Information technology payoff in e-business environments: an international perspective on value creation of e-business in the financial services industry, J.Manage. Inf. Syst., 21, 17, 10.1080/07421222.2004.11045797 · DOI · Paper page
- Espíndola, 2013, A model-based approach for data integration to improve maintenance management by mixed reality, Comput. Ind., 64, 376, 10.1016/j.compind.2013.01.002 · DOI
- Uva, 2018, Evaluating the effectiveness of spatial augmented reality in smart manufacturing: a solution for manual working stations, Int. J. Adv. Manuf. Technol., 94, 509, 10.1007/s00170-017-0846-4 · DOI · Paper page
- Alshawi, 2004, Integrating diverse ERP systems: a case study, J. Enterp. Inf. Manage., 17, 454, 10.1108/17410390410566742 · DOI
- Rashid, 2017, Enterprise systems’ life cycle in pursuit of resilient smart factory for emerging aircraft industry: a synthesis of Critical Success Factors’(CSFs), theory, knowledge gaps, and implications, Enterp. Inf. Syst., 39, 1
- Syberfeldt, 2017, Augmented reality smart glasses in the smart factory: product evaluation guidelines and review of available products, IEEE Access, 5, 9118, 10.1109/ACCESS.2017.2703952 · DOI · Paper page
- Angeles, 2014, Using the technology-organization-environment framework for analyzing nike's considered index green initiative, a decision support system-driven system, J. Manage. Sustain., 4, 96
- Premkumar, 2003, A meta-analysis of research on information technology implementation in small business, J. Organ. Comput. Electron. Commer., 13, 91, 10.1207/S15327744JOCE1302_2 · DOI · Paper page
- Oliveira, 2011, Literature review of information technology adoption models at firm level, Electron. J. Inf. Syst. Eval., 14, 110
- Fornell, 1981, Evaluating structural equation models with unobservable variables and measurement error, J. Mark. Res., 18, 39, 10.1177/002224378101800104 · DOI · Paper page
Cited by
Ghobakhloo, M., Iranmanesh, M., Grybauskas, A., Vilkas, M., & Petraitė, M. (2021) · Business Strategy and the Environment · doi:10.1002/bse.2867 · Cited by 462
Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations
Pillai, R., & Sivathanu, B. (2020) · Benchmarking: An International Journal · doi:10.1108/bij-04-2020-0186 · Cited by 422
Augmented reality in education: An overview of twenty-five years of research
Bacca-Acosta, J., Avila-Garzon, C., Kinshuk, ., Duarte, J., & Betancourt, J. (2021) · Contemporary Educational Technology · doi:10.30935/cedtech/10865 · Cited by 206
Adoption of AI-empowered industrial robots in auto component manufacturing companies
Pillai, R., Sivathanu, B., Mariani, M., Rana, N. P., Yang, B., & Dwivedi, Y. K. (2022) · Production Planning & Control · doi:10.1080/09537287.2021.1882689 · Cited by 195
Human-centered design of work systems in the transition to industry 4.0
Kadir, B. A., & Broberg, O. (2021) · Applied Ergonomics · doi:10.1016/j.apergo.2020.103334 · Cited by 177
Metadata
- Authors
- Masood, T., & Egger, J.
- Venue
- Robotics and Computer-Integrated Manufacturing
- Publisher
- Elsevier BV
- Published
- 2019-08
- Volume
- 58
- Pages
- 181-195
- ISSN
- 0736-5845 (ISSN-L)
- OpenAlex
- W2921205582
- Cited by
- 458
- References
- 10
- FWCI
- 26.59
- Type
- journal article
- Language
- en
- Open access
- green
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- Funders
- University of Cambridge
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Augmented reality in support of Industry 4.0—Implementation challenges and success factors. https://app.cochat.ai/papers/10.1016/j.rcim.2019.02.003
- The paper
- Masood, T., & Egger, J. (2019). Augmented reality in support of Industry 4.0—Implementation challenges and success factors. Robotics and Computer-Integrated Manufacturing. https://doi.org/10.1016/j.rcim.2019.02.003
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.