Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Fundamentals of All the Realities: Virtual, Augmented, Mediated, Multimediated, and Beyond Read chapter Read first chapter

2023 | OriginalPaper | Chapter

34. Digital Twin and Extended Reality: Strategic Approach and Practical Implementation

Authors : Roberto Rocca, Roman Felipe Bastidas Santacruz, Claudio Sassanelli, Paolo Rosa, Luca Fumagalli, Elisa Negri

Published in: Springer Handbook of Augmented Reality

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Nowadays, the digital transformation (driven by the Industry 4.0 (I4.0) paradigm) is becoming one of the most promising and valuable strategies to address business needs of manufacturing players in terms of agility, efficiency, and real-time reactivity. Among available digital (I4.0-based) technologies, Digital Twins (DTs) are described by researchers and practitioners as a key element in terms of smart manufacturing because of their potential to enable the shift from automation to autonomy. To this aim, the present chapter highlights characteristics and benefits of DTs, by proposing a strategic tool to support and guide Small- and Medium-sized Enterprises (SMEs) toward their adoption and exploitation. In addition, potentialities coming from the integration of both DTs and Extended Reality (ER) tools are shown through a laboratory application case.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Convergence of IoT and Augmented Reality
next chapter Digital Twins as Foundation for Augmented Reality Applications in Aerospace
Literature
1.
Ambra Cala, A. L., Boschi, F., Tavola, G., Taisch, M.: Migration towards digital manufacturing automation – An assessment approach. In: Proceedings – 2018 IEEE Industrial Cyber-Physical Systems, ICPS 2018 IEEE, St. Petersburg, 2018, pp. 714–719.
2.
ElMaraghy, H.A., Wiendahl, H.-P.: Changeable and Reconfigurable Manufacturing Systems. Springer, London (2009)
3.
Hofmann, E., Rüsch, M.: Industry 4.0 and the current status as well as future prospects on logistics. Comput. Ind. 89, 23–34 (2017)
4.
Calà, A., Boschi, F., Fantini, P., Lüder, A., Taisch, M.: Migration strategies towards the digital manufacturing automation. In: Soldatos, J., Lazaro, O., Cavadini, F. (eds.) The Digital Shopfloor: Industrial Automation in the Industry 4.0 Era, pp. 365–391. River Publisher (2019)
5.
Brettel, M., Friederichsen, N., Keller, M., Rosenberg, M.: How virtualization, decentralization and network building change the manufacturing landscape: an industry 4.0 perspective. Int. J. Sci. Eng. Technol. 8(1), 37–44 (2014)
6.
7.
Rocca, R., Rosa, P., Sassanelli, C., Fumagalli, L., Terzi, S.: Integrating virtual reality and digital twin in circular economy practices: a laboratory application case. Sustainability. 12(6), 2286 (2020)
8.
ANSI/ISA: Enterprise-Control System Integration – Part 1: Models and Terminology (2010).
9.
Chiarello, F., Trivelli, L., Bonaccorsi, A., Fantoni, G.: Extracting and mapping industry 4.0 technologies using wikipedia. Comput. Ind. 100(September 2018), 244–257 (2018)
10.
Culot, G., Nassimbeni, G., Orzes, G., Sartor, M.: Behind the definition of industry 4.0: analysis and open questions. Int. J. Prod. Econ. 226(January), 107617 (2020)
11.
Bastidas, R.F., Rocca, S.R., Negri, E., Fumagalli, L.: A review of features and applications of distributed ledger technologies for smart manufacturing. Int. J. Ind. Syst. Eng. (2021)
12.
Negri, E., Fumagalli, L., Macchi, M.: A review of the roles of digital twin in CPS-based production systems. Procedia Manuf. 11, 939–948 (2017)
13.
Cimino, C., Negri, E., Fumagalli, L.: Review of digital twin applications in manufacturing. Comput. Ind. 113, 103130 (2019)
14.
National Institute of Standards and Technology (NIST): Product definitions for smart manufacturing. (2018).
15.
ANSI/ISA: Enterprise-Control System Integration – Part 1: Models and Terminology. (2010).
16.
Pathfinder project: Pointing Out Research Priorities Leading To The Next Generation of Simulation and Forecasting Technologies (2014).
17.
Fumagalli, L., Pala, S., Garetti, M., Negri, E.: Ontology-based modeling of manufacturing and logistics systems for a new MES architecture. IFIP Adv. Inf. Commun. Technol. 438(PART 1), 192–200 (2014)
18.
Lee, J., Bagheri, B., Kao, H.A.: A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manuf. Lett. 3(January 2015), 18–23 (2015)
19.
Jazdi, N.: Cyber physical systems in the context of Industry 4.0. In: Proceedings – 2014 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR) 2014 IEEE, Cluj-Napoca, 2014, pp. 1–4.
20.
Baheti, R., Gill, H.: Cyber-physical systems. Impact Control Technol. 12(1), 161–166 (2011)
21.
Stock, T., Seliger, G.: Opportunities of sustainable manufacturing in industry 4.0. Procedia CIRP. 40, 536–541 (2016)
22.
de Sousa Jabbour, A.B.L., Jabbour, C.J.C., Filho, M.G., Roubaud, D.: Industry 4.0 and the circular economy: a proposed research agenda and original roadmap for sustainable operations. Ann. Oper. Res. 270, 273–286 (2018)
23.
Zorzo, A. F., Nunes, H. C., Lunardi, R. C., Michelin, R. A., Kanhere, S. S.: Dependable IoT Using Blockchain-Based Technology. In: 2018 Eighth Latin-American Symposium on Dependable Computing. IEEE, Foz do Iguaçu2018, pp. 1–19.
24.
Roblek, V., Meško, M., Krapež, A.: A complex view of industry 4.0. SAGE Open. 6(2), 1–11 (2016)
25.
Davis, J., Edgar, T., Porter, J., Bernaden, J., Sarli, M.: Smart manufacturing, manufacturing intelligence and demand-dynamic performance. Comput. Chem. Eng. 47(December 2012), 145–156 (2012)
26.
Lee, J., Kao, H., Yang, S.: Service innovation and smart analytics for Industry 4.0 and big data environment. Procedia CIRP. 16, 3–8 (2014)
27.
Yang, S., Raghavendra, M.R.A., Kaminski, J., Pepin, H.: Opportunities for industry 4.0 to support remanufacturing. Appl. Sci. 8(7), 1177 (2018)
28.
De Man, J.C., Strandhagen, J.O.: An industry 4.0 research agenda for sustainable business models. Procedia CIRP. 63, 721–726 (2017)
29.
Bressanelli, G., Adrodegari, F., Perona, M., Saccani, N.: Exploring how usage-focused business models enable circular economy through digital technologies. Sustain. 10(3) (2018)
30.
Pagoropoulos, A., Pigosso, D.C.A., McAloone, T.C.: The emergent role of digital technologies in the circular economy: a review. Procedia CIRP. 64, 19–24 (2017)
31.
Chang, M.M.L., Ong, S.K., Nee, A.Y.C.: Approaches and challenges in product disassembly planning for sustainability. Procedia CIRP. 60, 506–511 (2017)
32.
Chen, M., Mao, S., Liu, Y.: Big data: a survey. Mob. networks Appl. 19(2), 171–209 (2014)
33.
Fishman, G.S.: Principles of Discrete Event Simulation. John Wiley & Sons, Inc., New York, NY (1978)MATH
34.
Banks, J.: Handbook of simulation – Principles, Methodology, Advances, Applications, and Practice. Engineer & Management Press (1998)
35.
Goodall, P.A., Sharpe, R.G., West, A.A.: A data-driven simulation to support remanufacturing operations. Comput. Ind. 105, 48–60 (2019)
36.
Negahban, A., Smith, J.S.: Simulation for manufacturing system design and operation: literature review and analysis. J. Manuf. Syst. 33(2), 241–261 (2014)
37.
Weyer, S., Meyer, T., Ohmer, M., Gorecky, D., Zühlke, D.: Future modeling and simulation of CPS-based factories: an example from the automotive industry. IFAC-PapersOnLine. 49(31), 97–102 (2016)
38.
Legat, C., Seitz, C., Lamparter, S., Feldmann, S.: Semantics to the shop floor: Towards ontology modularization and reuse in the automation domain. IFAC Proc. 19, 3444–3449 (2014)
39.
Negri, E., Fumagalli, L., Garetti, M., Tanca, L.: Requirements and languages for the semantic representation of manufacturing systems. Comput. Ind. 81, 55–66 (2016)
40.
Posada, J., Toro, C., Barandiaran, I., Oyarzun, D., Stricker, D., De Amicis, R., Pinto, E.B., Eisert, P., Döllner, J., I.: Vallarino: visual computing as a key enabling technology for industrie 4.0 and industrial internet. IEEE Comput. Graph. Appl. 35(2), 26–40 (2015)
41.
Wang, X.V., Wang, L.: Digital twin-based WEEE recycling, recovery and remanufacturing in the background of industry 4.0. Int. J. Prod. Res. 57(12), 3892–3902 (2019)
42.
Boud, A. C., Haniff, D. J., Baber, C., Steiner, S. J.: Virtual reality and augmented reality as a training tool for assembly tasks. In: Proceedings of the international conference on information vision. IEEE, London, 1999, pp. 32–36.
43.
Ke, S., Xiang, F., Zhang, Z., Zuo, Y.: A enhanced interaction framework based on VR, AR and MR in digital twin. In: 11th CIRP conference on industrial product-service systems. Elsevier B.V., 2019, pp. 753–758.
44.
Yoh, M. S.: The reality of virtual reality. In: Proceedings – 7th international conference on virtual systems and multimedia, VSMM 2001. IEEE, Berkeley, 2001, pp. 666–674.
45.
Latta, J.N., Oberg, D.J.: A conceptual virtual reality model. IEEE Comput. Graph. Appl. 14(1), 23–29 (1994)
46.
Jones, D., Snider, C., Nassehi, A., Yon, J., Hicks, B.: Characterising the digital twin: a systematic literature review. CIRP J. Manuf. Sci. Technol. 29, 36–52 (2020)
47.
Tao, F., Zhang, M.: Digital twin shop-floor: a new shop-floor paradigm towards smart manufacturing. IEEE Access. 5, 20418–20427 (2017)
48.
Roldán, J.J., Crespo, E., Martín-Barrio, A., Peña-Tapia, E., Barrientos, A.: A training system for Industry 4.0 operators in complex assemblies based on virtual reality and process mining. Robot. Comput. Integr. Manuf. 59, 305–316 (2019)
49.
Havard, V., Jeanne, B., Lacomblez, M., Baudry, D.: Digital twin and virtual reality: a co-simulation environment for design and assessment of industrial workstations. Prod. Manuf. Res. 7(1), 472–489 (2019)
50.
West, T. D. Blackburn, M.: Is digital thread/digital twin affordable? a systemic assessment of the cost of DoD’s latest Manhattan Project. Procedia Computer Sciences. (Elsevier B.V., Chicago, 2017), pp. 47–56.
51.
Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., Sui, F.: Digital twin-driven product design, manufacturing and service with big data. Int. J. Adv. Manuf. Technol. 94(9–12), 3563–3576 (2018)
52.
Carmigniani, J., Furht, B., Anisetti, M., Ceravolo, P., Damiani, E., Ivkovic, M.: Augmented reality technologies, systems and applications. Multimed. Tools Appl. 51(1), 341–377 (2011)
53.
Wang, P., Zhang, S., Billinghurst, M., Bai, X., He, W., Wang, S., Sun, M., Zhang, X.: A comprehensive survey of AR/MR-based co-design in manufacturing. Eng. Comput. 36(4), 1715–1738 (2020)
54.
Tao, F., Zhang, M., Nee, A. Y. C. Y. C.: Digital twin and virtual reality and augmented reality/mixed reality. In: Digital Twin Driven Smart Manufacturing. Elsevier, 2019.
55.
Rabah, S., Assila, A., Khouri, E., Maier, F., Ababsa, F., Bourny, V., Maier, P., Mérienne, F.: Towards improving the future of manufacturing through digital twin and augmented reality technologies. Procedia Manuf. 17, 460–467 (2018)
56.
Rosen, R., Von Wichert, G., Lo, G., Bettenhausen, K.D., Von Wichert, G., Lo, G., Bettenhausen, K.D., Von Wichert, G., Lo, G., Bettenhausen, K.D.: About the importance of autonomy and digital twins for the future of manufacturing. IFAC-PapersOnLine. 28(3), 567–572 (2015)
57.
Schroeder, G., Steinmetz, C., Pereira, C. E., Muller, I., Garcia, N., Espindola, D., Rodrigues, R.: Visualising the digital twin using web services and augmented reality. In: 2016 IEEE 14th international conference on industrial informatics. IEEE, Poitiers, 2016, pp. 522–527.
58.
Shao, G., Helu, M.: Framework for a digital twin in manufacturing: Scope and requirements. Manuf. Lett. 24, 105–107 (2020)
59.
Kritzinger, W., Karner, M., Traar, G., Henjes, J., Sihn, W.: Digital Twin in manufacturing: a categorical literature review and classification. IFAC-PapersOnLine. 51(11), 1016–1022 (2018)
60.
Kitchenham, B. Charters, S.: Guidelines for performing Systematic Literature Reviews in SE (2007).
61.
Pollock, A., Berge, E.: How to do a systematic review. Int. J. Stroke. 13(2), 138–156 (2018)
62.
Macchi, M., Roda, I., Negri, E., Fumagalli, L.: Exploring the role of Digital Twin for asset lifecycle management. IFAC-PapersOnLine. 51(11), 790–795 (2018)
63.
Shangguan, D., Chen, L., Ding, J.: A hierarchical digital twin model framework for dynamic cyber-physical system design. In: ICMRE’19: the 5th international conference on mechatronics and robotics engineering. Association for Computing Machinery, Rome, 2019), pp. 123–129.
64.
Liu, Z., Meyendorf, N., Mrad, N.: The role of data fusion in predictive maintenance using digital twin. In: AIP Conference Proceedings. American Institute of Physics Inc., 2018, pp. 1–6.
65.
Erikstad, S. O.: Merging Physics, Big Data Analytics and Simulation for the Next-Generation Digital Twins. In: HIPER 2017, High-Performance Marine Vehicles. Zevenwacht, 2017, pp. 139–149.
66.
He, X., Ai, Q., Qiu, R. C., Zhang, D.: Preliminary Exploration on Digital Twin for Power Systems: Challenges, Framework, and Applications. (2019).
67.
Lu, Q., Xie, X., Heaton, J., Parlikad, A.K., Schooling, J.: From BIM towards digital twin: Strategy and future development for smart asset management. In: Borangiu, T., Trentesaux, D., Leitão, P., Boggino, A.G., Botti, V. (eds.) SOHOMA 2019 Serv. Oriented, Holonic Multi-agent Manuf. Syst. Ind. Futur, pp. 392–404. Springer (2020)
68.
Lee, J., Azamfar, M., Singh, J., Siahpour, S.: Integration of digital twin and deep learning in cyber-physical systems: towards smart manufacturing. IET Collab. Intell. Manuf. 2(1), 34–36 (2020)
69.
Aivaliotis, P., Georgoulias, K., Alexopoulos, K.: Using digital twin for maintenance applications in manufacturing: State of the Art and Gap analysis. In: 2019 IEEE International Conference on Engineering, Technology and Innovation. IEEE, Valbonne Sophia-Antipolis, 2019.
70.
Rodič, B.: Industry 4.0 and the new simulation modelling paradigm. Organizacija. 50(3), 193–207 (2017)
71.
Liu, Q., Zhang, H., Leng, J., Chen, X.: Digital twin-driven rapid individualised designing of automated flow-shop manufacturing system. Int. J. Prod. Res. 57(12), 3903–3919 (2019)
72.
Alam, K.M., El Saddik, A.: C2PS: a digital twin architecture reference model for the cloud-based cyber-physical systems. IEEE Access. 5, 2050–2062 (2017)
73.
Guo, J., Zhao, N., Sun, L., Zhang, S.: Modular based flexible digital twin for factory design. J. Ambient Intell. Humaniz. Comput. 10(3), 1189–1200 (2019)
74.
Grieves, M.: Origins of the Digital Twin Concept (2016).
75.
Biesinger, F., Weyrich, M.: The Facets of Digital Twins in Production and the Automotive Industry. In: 2019 23rd International Conference on Mechatronics Technology. IEEE, Salerno, 2019.
76.
Rasheed, A., San, O., Kvamsdal, T.: Digital twin: Values, challenges and enablers from a modeling perspective. IEEE Access. 8, 21980–22012 (2020)
77.
Autiosalo, J., Vepsalainen, J., Viitala, R., Tammi, K.: A feature-based framework for structuring industrial digital twins. IEEE Access. 8, 1193–1208 (2020)
78.
Qi, Q., Tao, F.: Digital twin and big data towards smart manufacturing and industry 4.0: 360 degree comparison. IEEE Access. 6, 3585–3593 (2018)
79.
Rosen, R., Boschert, S., Sohr, A.: Next generation digital twin. atp Mag. 60(10), 86–96 (2018)
80.
Tao, F., Zhang, H., Liu, A., Nee, A.Y.C.: Digital twin in industry: state-of-the-art. IEEE Trans. Ind. Informatics. 15(4), 2405–2415 (2019)
81.
Lu, Y., Liu, C., Wang, K.I.K., Huang, H., Xu, X.: Digital Twin-driven smart manufacturing: connotation, reference model, applications and research issues. Robot. Comput. Integr. Manuf. 61, 101837 (2020)
82.
M. Grieves & J. Vickers: Digital twin: Mitigating unpredictable, undesirable emergent behavior in complex systems. In: Transdisciplinary Perspectives on Complex Systems: New Findings and Approaches. Springer International Publishing, 2016, pp. 85–113.
83.
Fuller, A., Fan, Z., Day, C., Barlow, C.: Digital twin: enabling technologies, challenges and open research. IEEE Access. 8, 108952–108971 (2020)
84.
Tao, F., Qi, Q., Wang, L., Nee, A.Y.C.: Digital twins and cyber–physical systems toward smart manufacturing and industry 4.0: correlation and comparison. Engineering. 5(4), 653–661 (2019)
85.
Martinez, V., Ouyang, A., Neely, A., Burstall, C., Bisessar, D.: Service business model innovation : the digital twin technology. EurOMA. (2018)
86.
Malek, Y. N., Kharbouch, A., Khoukhi, H. El, Bakhouya, M., De Florio, V., El Ouadghiri, D., Latre, S., Blondia, C.: On the use of IoT and Big Data Technologies for Real-time Monitoring and Data Processing. In: 8th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN 2017). Elsevier B.V., Procedia Computer Science, 2017, pp. 429–434.
87.
Qi, Q., Tao, F., Zuo, Y., Zhao, D.: Digital Twin Service towards Smart Manufacturing. In: 51st CIRP conference on manufacturing systems. Elsevier B.V., Procedia CIRP, 2018, pp. 237–242.
88.
Wache, H. Dinter, B.: The Digital Twin – Birth of an Integrated System in the Digital Age. In: Proceedings of the 53rd Hawaii International Conference on System Sciences. International Conference on System Sciences, Maui, Hawaii, 2020.
89.
Madni, A., Madni, C., Lucero, S.: Leveraging digital twin technology in model-based systems engineering. Systems. 7(1), 1–13 (2019)
90.
Modoni, G. E., Caldarola, E. G., Sacco, M., Terkaj, W.: Synchronizing physical and digital factory: Benefits and technical challenges. In: Procedia CIRP. Elsevier B.V., Naples, 2019, pp. 472–477.
91.
Bolton, R.N., McColl-Kennedy, J.R., Cheung, L., Gallan, A., Orsingher, C., Witell, L., Zaki, M.: Customer experience challenges: bringing together digital, physical and social realms. J. Serv. Manag. 29(5), 776–808 (2018)
92.
Qi, Q., Tao, F., Hu, T., Anwer, N., Liu, A., Wei, Y., Wang, L., Nee, A.Y.C.: Enabling technologies and tools for digital twin. J. Manuf. Syst. (2019)
93.
Melesse, T. Y., Di Pasquale, V., Riemma, S.: Digital twin models in industrial operations: a systematic literature review. In: Procedia Manufacturing. Elsevier B.V., 2020, pp. 267–272.
94.
He, B., Bai, K.J.: Digital twin-based sustainable intelligent manufacturing: a review. Adv. Manuf. 1–21 (2020)
95.
Xu, J., Huang, E., Hsieh, L., Lee, L.H., Jia, Q.S., Chen, C.H.: Simulation optimization in the era of Industrial 4.0 and the Industrial Internet. J. Simul. 10(4), 310–320 (2016)
96.
Uhlemann, T. H. J., Lehmann, C., Steinhilper, R.: The digital twin: realizing the cyber-physical production system for industry 4.0. In: The 24th CIRP conference on life cycle engineering. Elsevier B.V., 2017, pp. 335–340.
97.
Liu, J., Zhou, H., Tian, G., Liu, X., Jing, X.: Digital twin-based process reuse and evaluation approach for smart process planning. Int. J. Adv. Manuf. Technol. 100(5–8), 1619–1634 (2019)
98.
Uhlemann, T.H.J., Schock, C., Lehmann, C., Freiberger, S., Steinhilper, R.: The digital twin: demonstrating the potential of real time data acquisition in production systems. Procedia Manuf. 9, 113–120 (2017)
99.
Zhuang, C., Liu, J., Xiong, H.: Digital twin-based smart production management and control framework for the complex product assembly shop-floor. Int. J. Adv. Manuf. Technol. 96(1–4), 1149–1163 (2018)
100.
He, R., Chen, G., Dong, C., Sun, S., Shen, X.: Data-driven digital twin technology for optimized control in process systems. ISA Trans. 95, 221–234 (2019)
101.
Min, Q., Lu, Y., Liu, Z., Su, C., Wang, B.: Machine Learning based Digital Twin Framework for Production Optimization in Petrochemical Industry. Int. J. Inf. Manage. 49, 502–519 (2019)
102.
Vachalek, J., Bartalsky, L., Rovny, O., Sismisova, D., Morhac, M., Loksik, M.: The digital twin of an industrial production line within the industry 4.0 concept. In: 2017 21st international conference on process control. IEEE, Strbske Pleso, 2017, pp. 258–262.
103.
Zhang, H., Liu, Q., Chen, X., Zhang, D., Leng, J.: A digital twin-based approach for designing and multi-objective optimization of hollow glass production line. IEEE Access. 5, 26901–26911 (2017)
104.
Bao, J., Guo, D., Li, J., Zhang, J.: The modelling and operations for the digital twin in the context of manufacturing. Enterp. Inf. Syst. 13(4), 534–556 (2019)
105.
Wang, Y., Wang, S., Yang, B., Zhu, L., Liu, F.: Big data driven hierarchical digital twin predictive remanufacturing paradigm: architecture, control mechanism, application scenario and benefits. J. Clean. Prod. 248, 119299 (2020)
106.
Kostenko, D., Kudryashov, N., Maystrishin, M., Onufriev, V., Potekhin, V., Vasiliev, A.: Digital twin applications: diagnostics, optimisation and prediction. In: Annual DAAAM Proceedings International DAAAM Symposim, 574–0581 (2018).
107.
Papacharalampopoulos, A., Giannoulis, C., Stavropoulos, P., Mourtzis, D.: A digital twin for automated root-cause search of production alarms based on KPIs aggregated from IoT. Appl. Sci. 10(7), 2377 (2020)
108.
Ding, K., Chan, F.T.S., Zhang, X., Zhou, G., Zhang, F.: Defining a digital twin-based cyber-physical production system for autonomous manufacturing in smart shop floors. Int. J. Prod. Res. 57(20), 6315–6334 (2019)
109.
Leng, J., Zhang, H., Yan, D., Liu, Q., Chen, X., Zhang, D.: Digital twin-driven manufacturing cyber-physical system for parallel controlling of smart workshop. J. Ambient Intell. Humaniz. Comput. 10(3), 1155–1166 (2019)
110.
Stojanovic, N., Milenovic, D.: Data-driven Digital Twin approach for process optimization: an industry use case. In: 2018 IEEE international conference on Big Data (Big Data). IEEE, Seattle 2019, pp. 4202–4211.
111.
Zhao, P., Liu, J., Jing, X., Tang, M., Sheng, S., Zhou, H., Liu, X.: The modeling and using strategy for the digital twin in process planning. IEEE Access. 8, 41229–41245 (2020)
112.
Fang, Y., Peng, C., Lou, P., Zhou, Z., Hu, J., Yan, J.: Digital-twin-based job shop scheduling toward smart manufacturing. IEEE Trans. Ind. Informatics. 15(12), 6425–6435 (2019)
113.
Negri, E., Fumagalli, L., Cimino, C., MacChi, M.: FMU-supported simulation for CPS digital twin. In: 7th International conference on Changeable, Agile, Reconfigurable and Virtual Production. (CARV2018), Procedia Manufacturing. Elsevier B.V., 2019, pp. 201–206.
114.
Lu, Y., Xu, X.: Resource virtualization: a core technology for developing cyber-physical production systems. J. Manuf. Syst. 47, 128–140 (2018)
115.
Zhu, Z., Liu, C., Xu, X.: Visualisation of the digital twin data in manufacturing by using augmented reality. Procedia CIRP. 81, 898–903 (2019)
116.
Liu, C., Jiang, P., Jiang, W.: Web-based digital twin modeling and remote control of cyber-physical production systems. Robot. Comput. Integr. Manuf. 64, 101956 (2020)
117.
Zhou, G., Zhang, C., Li, Z., Ding, K., Wang, C.: Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing. Int. J. Prod. Res. 58(4), 1034–1051 (2020)
118.
Nikolakis, N., Alexopoulos, K., Xanthakis, E., Chryssolouris, G.: The digital twin implementation for linking the virtual representation of human-based production tasks to their physical counterpart in the factory-floor. Int. J. Comput. Integr. Manuf. 32(1), 1–12 (2019)
119.
Miller, A.M.D., Alvarez, R., Hartman, N.: Towards an extended model-based definition for the digital twin. Comput. Aided. Des. Appl. 15(6), 880–891 (2018)
120.
Zheng, Y., Yang, S., Cheng, H.: An application framework of digital twin and its case study. J. Ambient Intell. Humaniz. Comput. 10(3), 1141–1153 (2019)
121.
Zhang, H., Ma, L., Sun, J., Lin, H., Thürer, M.: Digital twin in services and industrial product service systems: Review and analysis. In: 11th CIRP Conference on Industrial Product-Service Systems Procedia CIRP. Elsevier B.V., 2019, pp. 57–60.
122.
Söderberg, R., Wärmefjord, K., Carlson, J.S., Lindkvist, L.: Toward a Digital Twin for real-time geometry assurance in individualized production. CIRP Ann. – Manuf. Technol. 66(1), 137–140 (2017)
123.
Kritzler, M., Funk, M., Michahelles, F., Rohde, W.: The virtual twin: controlling smart factories using a spatially-correct augmented reality representation. ACM Int. Conf. Proceeding Ser. (2017)
124.
Henderson, S. J., Feiner, S.: Evaluating the benefits of augmented reality for task localization in maintenance of an armored personnel carrier turret. In: Science & Technology Proceedings,– IEEE 2009 International Symposium on Mixed and Augmented Reality. ISMAR 2009, 135–144 (2009).
125.
Revetria, R., Tonelli, F., Damiani, L., Demartini, M., Bisio, F., Peruzzo, N.: A real-time mechanical structures monitoring system based on digital Twin, IOT and augmented reality. Simul. Ser. 51(1) (2019)
126.
Cai, Y., Wang, Y., Burnett, M.: Using augmented reality to build digital twin for reconfigurable additive manufacturing system. J. Manuf. Syst. 56(April), 598–604 (2020)
127.
Aheleroff, S., Xu, X., Zhong, R.Y., Lu, Y.: Digital Twin as a Service (DTaaS) in Industry 4.0: An Architecture Reference Model. Adv. Eng. Informatics. 47(October 2020), 101225 (2021)
128.
Qiu, C., Zhou, S., Liu, Z., Gao, Q., Tan, J.: Digital assembly technology based on augmented reality and digital twins: a review. Virtual Real. Intell. Hardw. 1(6), 597–610 (2019)
129.
Liu, S., Lu, S., Li, J., Sun, X., Lu, Y., Bao, J.: Machining process-oriented monitoring method based on digital twin via augmented reality. Int. J. Adv. Manuf. Technol. (2021)
130.
Rabah, S., Assila, A., Khouri, E., Maier, F., Ababsa, F., Bourny, V., Maier, P., Mérienne, F.: Towards improving the future of manufacturing through digital twin and augmented reality technologies. Procedia Manuf. 17, 460–467 (2018)
131.
Mandolla, C., Petruzzelli, A.M., Percoco, G., Urbinati, A.: Building a digital twin for additive manufacturing through the exploitation of blockchain: a case analysis of the aircraft industry. Comput. Ind. 109, 134–152 (2019)
132.
Roda, I., Macchi, M., Albanese, S.: Building a Total Cost of Ownership model to support manufacturing asset lifecycle management. Prod. Plan. Control. 31(1), 19–37 (2020)
133.
Yusupbekov, N., Abdurasulov, F., Adilov, F., Ivanyan, A.: Concepts and methods of “Digital Twins” models creation in industrial asset performance management systems. In: Kahraman, C., Cevik Onar, S., Oztaysi, B., Sari, I., Cebi, S. (eds.) International Conference on Intelligent and Fuzzy Systems INFUS 2020, pp. 1589–1595. Springer, Cham (2021)
134.
Roda, I., Parlikad, A.K., Macchi, M., Garetti, M.: A framework for implementing value-based approach in asset management. In: Koskinen, K. (ed.) Proceedings of the 10th World Congress on Engineering Asset Management. WCEAM 2015, pp. 487–495. Springer, Charm (2016)
135.
Park, K.T., Nam, Y.W., Lee, H.S., Im, S.J., Do Noh, S., Son, J.Y., Kim, H.: Design and implementation of a digital twin application for a connected micro smart factory. Int. J. Comput. Integr. Manuf. 32(6), 596–614 (2019)
136.
Durão, L. F. C. S., Haag, S., Anderl, R., Schützer, K., Zancul, E.: Digital twin requirements in the context of industry 4.0. In: IFIP Advances in Information and Communication Technology. Springer New York LLC, 2018, pp. 204–214.
137.
Schleich, B., Anwer, N., Mathieu, L., Wartzack, S.: Shaping the digital twin for design and production engineering. CIRP Ann. – Manuf. Technol. 66(1), 141–144 (2017)
138.
Farooq, M.U., Waseem, M., Mazhar, S., Khairi, A., Kamal, T.: A review on Internet of Things (IoT). Int. J. Comput. Appl. 113(1), 1–7 (2015)
139.
Lee, J., Azamfar, M., Singh, J.: A blockchain enabled cyber-physical system architecture for industry 4.0 manufacturing systems. Manuf. Lett. 20, 34–39 (2019)
140.
Tao, F., Sui, F., Liu, A., Qi, Q., Zhang, M., Song, B., Guo, Z., Lu, S.C.Y., Nee, A.Y.C.: Digital twin-driven product design framework. Int. J. Prod. Res. 57(12), 3935–3953 (2019)
141.
Rocca, R., Tavola, G., Boschi, F., Fantini, P., Taisch, M., Lambruschini, V. R.: Business Case Evaluation Methodology ( BCEM ) for Factories Digitalization. In: The Thirteenth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies. UBICOMM 2019 Politecnico di Milano, Porto, 2019, pp. 134–141.
142.
Brady, T., Rush, H., Hobday, M., Davies, A., Probert, D., Banerjee, S.: Tools for technology management: an academic perspective. Technovation. 17(8), 417–426 (1997)
143.
Bozarth, C., Edwards, S.: The impact of market requirements focus and manufacturing characteristics focus on plant performance. J. Oper. Manag. 15(3), 161–180 (1997)
144.
145.
146.
Smith, J.S.: Survey on the use of simulation for manufacturing system design and operation. J. Manuf. Syst. 22(2), 157–171 (2003)
147.
Festo: Festo Didactics. CIROS software 2018. (2018).
148.
Colombo, A.W., Bangemann, T., Karnouskos, S., Delsing, J., Stluka, P., Harrison, R., Jammes, F., Lastra, J.L.M.: Industrial Cloud-Based Cyber-Physical Systems. Springer, Cham (2014)
149.
Mintzberg, H.: The strategy concept I: five Ps for strategy. Calif. Manage. Rev. 30(1), 11–24 (1987)
Metadata
Title
Digital Twin and Extended Reality: Strategic Approach and Practical Implementation
Authors
Roberto Rocca
Roman Felipe Bastidas Santacruz
Claudio Sassanelli
Paolo Rosa
Luca Fumagalli
Elisa Negri
Copyright Year
2023
Book
Springer Handbook of Augmented Reality

Print ISBN: 978-3-030-67821-0

Electronic ISBN: 978-3-030-67822-7

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-3-030-67822-7_34

Premium Partner

    Image Credits