Autonomous, context-aware, adaptive Digital Twins—State of the art and roadmap

Computers in Industry - Tập 133 - Trang 103508 - 2021
Karl Hribernik1, Giacomo Cabri2, Federica Mandreoli2, Gregoris Mentzas3
1BIBA - Bremer Institut für Produktion und Logistik GmbH at the University of Bremen, Hochschulring 20, 28359 Bremen, Germany
2Dipartimento di Scienze Fisiche Informatiche e Matematiche Universita' di Modena e Reggio Emilia, Italy
3Information Management Unit (IMU), Institute of Communication and Computer Systems (ICCS), National Technical University of Athens (NTUA), Greece

Tài liệu tham khảo

Alam, 2017, C2PS: a Digital Twin architecture reference model for the cloud-based cyber-physical systems, IEEE Access, 5, 2050, 10.1109/ACCESS.2017.2657006 Alexopoulos, 2016, A concept for context-aware computing in manufacturing: the white goods case, Int. J. Comput. Integr. Manuf., 29, 839, 10.1080/0951192X.2015.1130257 Anderl, 2018, Digital twin technology – an approach for Industrie 4.0 vertical and horizontal lifecycle integration, It - Inf. Technol., 60, 125 Antsaklis, 1991, An introduction to autonomous control systems, IEEE Control Syst., 11, 5, 10.1109/37.88585 Attanasio, 2006, Auction algorithms for decentralized parallel machine scheduling, Parallel Comput., 32, 701, 10.1016/j.parco.2006.03.002 autonomy | Definition of autonomy in English by Lexico Dictionaries, (n.d.). https://www.lexico.com/en/definition/autonomy (Accessed 9 July 2019). Azouz, 2019, Adaptive smart card-based pull control systems in context-aware manufacturing systems: training a neural network through multi-objective simulation optimization, Appl. Soft Comput. J., 75, 46, 10.1016/j.asoc.2018.10.051 Bao, 2019, The modelling and operations for the digital twin in the context of manufacturing, Enterp. Model. Inf. Syst. Archit., 13, 534, 10.1080/17517575.2018.1526324 Bergweiler, 2016, Smart factory systems-fostering cloud-based manufacturing based on self-monitoring cyber-physical systems, J. Adv. Syst. Meas., 9, 91 Bicocchi, 2018, Dealing with data and software interoperability issues in digital factories, 13 Bicocchi, 2019, Dynamic digital factories for agile supply chains: An architectural approach, JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION, 15, 110, 10.1016/j.jii.2019.02.001 Bisio, 2018, Exploiting context-aware capabilities over the internet of things for industry 4.0 applications, IEEE Netw., 32, 101, 10.1109/MNET.2018.1700355 Borangiu, 2019, Digital transformation of manufacturing through cloud services and resource virtualization, Comput. Ind., 108, 150, 10.1016/j.compind.2019.01.006 Boschert, 2016, Digital Twin—the simulation aspect, 59 Botti, 2008, Holonic manufacturing systems, 7 Bousdekis, 2015, A proactive decision making framework for condition-based maintenance, Ind. Manag. Data Syst., 115, 1225, 10.1108/IMDS-03-2015-0071 Bousdekis, 2017, 416 Bousdekis, 2019, A unified architecture for proactive maintenance in manufacturing enterprises, 307 Cardin, 2019, Classification of cyber-physical production systems applications: proposition of an analysis framework, Comput. Ind., 104, 11, 10.1016/j.compind.2018.10.002 Chinesta, 2020, Virtual, digital and hybrid twins: a new paradigm in data-based engineering and engineered data, Arch. Comput. Methods Eng., 27, 105, 10.1007/s11831-018-9301-4 Cimino, 2019, Review of digital twin applications in manufacturing, Comput. Ind., 113, 10.1016/j.compind.2019.103130 CoBuilder, 2018 Cronrath, 2019, Enhancing digital twins through reinforcement learning, IEEE Int. Conf. Autom. Sci. Eng., IEEE Computer Society, 293 S.M. Dambrot, Symbiotic Autonomous Systems, Digital Twins and Artificial Intelligence: Emergence and Evolution, n.d., http://mondodigitale.aicanet.net/2019-1/articoli/03_MD80_Symbiotic_Autonomous_Digital_Twins_and_Artificial_Intelligence.pdf (Accessed 3 July 2020). de Visser, 2011, Adaptive aiding of human-robot teaming, J. Cogn. Eng. Decis. Mak., 5, 209, 10.1177/1555343411410160 El Saddik, 2018, Digital Twins: the convergence of multimedia technologies, IEEE Multimed., 25, 87, 10.1109/MMUL.2018.023121167 Elwany, 2008, Sensor-driven prognostic models for equipment replacement and spare parts inventory, IIE Trans. (Institute Ind. Eng., 40, 629 Engel, 2012, A basic model for proactive event-driven computing, 107 Erdős, 2020, Transformation of robotic workcells to digital twins, CIRP Ann., 69, 149, 10.1016/j.cirp.2020.03.003 Fantini, 2016, Exploring the integration of the human as a flexibility factor in CPS enabled manufacturing environments: methodology and results, IECON Proc. (Industrial Electron. Conf.) Främling, 2003, Product agents for handling information about physical objects, Rep. Lab. Inf. Process. Sci. Ser. B, 153, 1 Gabor, 2016, A simulation-based architecture for smart cyber-physical systems, Proc. - 2016 IEEE Int. Conf. Auton. Comput. ICAC 2016, IEEE, 374 Gaham, 2015, Human-in-the-loop cyber-physical production systems control (HiLCP2sC): a multi-objective interactive framework proposal, Stud. Comput. Intell., 594, 315, 10.1007/978-3-319-15159-5_29 Gebhardt, 2011, Exploitation of manufacturing flexibilities in decision methods for autonomous control of production processes: findings from industrial practice and theoretical analysis, 169 Giret, 2004, Holons and agents, J. Intell. Manuf., 15, 645, 10.1023/B:JIMS.0000037714.56201.a3 Glaessgen, 2012 Gockel, 2012 Gonçalves, 2018, Adaptability in smart manufacturing systems, 36 Gorecky, 2014, Human-machine-interaction in the industry 4.0 era, 289 Grieves, 2016, Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems, 85 Guo, 2019, Modular based flexible digital twin for factory design, J. Ambient Intell. Humaniz. Comput., 10, 1189, 10.1007/s12652-018-0953-6 Hartmann, 2018, Model order reduction a key technology for digital twins, 167 He, 2018, Statistical process monitoring as a big data analytics tool for smart manufacturing, J. Process Control, 92, 333 He, 2019, Data-driven digital twin technology for optimized control in process systems, ISA Trans., 95, 221, 10.1016/j.isatra.2019.05.011 Hochhalter, 2014, 10 Hribernik, 2005, A concept for product-instance-centric information management, IEEE Int. Technol. Manag. Conf. ICE 2005, 2016 Hribernik, 2018, Towards a unified predictive maintenance system - a use case in production logistics in aeronautics, Procedia Manuf., 16, 131, 10.1016/j.promfg.2018.10.168 Hülsmann, 2005, Autonomous cooperation in international- supply-networks the need for a shift from centralized planning to decentralized decision Making in logistic processes, 243 Hülsmann, 2007 Hülsmann, 2009, Collaborative transportation planning in complex adaptive logistics systems: a complexity science-based analysis of decision-making problems of “groupage systems” in: complex 2009, 1160 Inagaki, 2003, Hanbook of cognitive task design, 8 adaptive automation: sharing and trading of control, 147 Jaekel, 2020, Ensure OPC-UA interfaces for digital plug-and-produce, 44 Joo, 2019, Formalizing human–Machine interactions for adaptive automation in smart manufacturing, IEEE Trans. Human-Machine Syst., 49, 529, 10.1109/THMS.2019.2903402 Josifovska, 2019, Reference framework for digital twins within cyber-physical systems, 25 Kapteyn, 2020, Data-driven physics-based digital twins via a library of component-based reduced-order models, Int. J. Numer. Methods Eng., 1 Kassner, 2017, The social factory: connecting people, machines and data in manufacturing for context-aware exception escalation, Proc. 50th Hawaii Int. Conf. Syst. Sci., Hawaii International Conference on System Sciences, 10.24251/HICSS.2017.202 Klein, 2019, Towards an approach integrating various levels of data analytics to exploit product-usage information in product development, 2627 Koulamas, 2018, Cyber-physical systems and digital twins in the industrial internet of things [cyber-physical systems], Computer (Long. Beach. Calif)., 51, 95 Kritzinger, 2018, Digital Twin in manufacturing: a categorical literature review and classification, IFAC-Papers On Line, 51, 1016, 10.1016/j.ifacol.2018.08.474 Kulvatunyou, 2018, The industrial ontologies foundry proof-of-concept project, 402, 10.1007/978-3-319-99707-0_50 Lee, 2013, Enhancement of industrial monitoring systems by utilizing context awareness, 277 Lee, 2013, Predictive manufacturing system - trends of next-generation production systems, Ifac Proc. Vol., 46, 150, 10.3182/20130522-3-BR-4036.00107 Lee, 2016, An energy management framework for smart factory based on context-awareness, 685 Leitão, 2003, 59 Leng, 2019, Digital twin-driven manufacturing cyber-physical system for parallel controlling of smart workshop, J. Ambient Intell. Humaniz. Comput., 10, 1155, 10.1007/s12652-018-0881-5 Lindberg, 1990, Strategic manufacturing management: a proactive approach, Int. J. Oper. Prod. Manag., 10, 94, 10.1108/01443579010001221 Louie, 2010, Robert Rosen’s anticipatory systems, Foresight, 12, 18, 10.1108/14636681011049848 Lu, 2017, Industry 4.0: a survey on technologies, applications and open research issues, J. Ind. Inf. Integr., 6, 1 Lu, 2019 Lu, 2020, Digital Twin-driven smart manufacturing: connotation, reference model, applications and research issues, Robot. Comput. Manuf., 61, 101837, 10.1016/j.rcim.2019.101837 Lucke, 2008, Smart factory - a step towards the next generation of manufacturing Lützenberger, 2016, Improving product-service systems by exploiting information from the usage phase. A case study, Procedia CIRP, 47, 376, 10.1016/j.procir.2016.03.064 Madni, 1982, A trainable on-line model of the human operator in information acquisition tasks, IEEE Trans. Syst. Man Cybern., 12, 504, 10.1109/TSMC.1982.4308855 Madni, 2019, Leveraging digital twin technology in model-based systems engineering, Systems, 7, 7, 10.3390/systems7010007 Maes, 1993, Modeling adaptive autonomous agents, Artif. Life, 1, 135, 10.1162/artl.1993.1.1_2.135 Mandelbaum, 1978 Mourtzis, 2014, Machine availability monitoring for adaptive holistic scheduling: a conceptual framework for mass customization, Procedia CIRP, 25, 406, 10.1016/j.procir.2014.10.056 Mullen, 2009, A review of ant algorithms, Expert Syst. Appl., 36, 9608, 10.1016/j.eswa.2009.01.020 Müller, 2012, Autonomous cognitive systems in real-world environments: less control, more flexibility and better interaction, Cognit. Comput., 4, 212, 10.1007/s12559-012-9129-4 Nadin, 2017, Predictive and anticipatory computing, 643 Nunna, 2015, Enabling real-time context-aware collaboration through 5G and mobile edge computing, 601 Otto, 2018, Industrial data space, 113 Pachter, 1998, Challenges of autonomous control, IEEE Control Syst., 18, 92, 10.1109/37.710883 Park, 2011, An autonomous manufacturing system for adapting to disturbances, Int. J. Adv. Manuf. Technol., 56, 1159, 10.1007/s00170-011-3229-2 Park, 2020, Digital twin-based cyber physical production system architectural framework for personalized production, Int. J. Adv. Manuf. Technol., 106, 1787, 10.1007/s00170-019-04653-7 Passino, 1995, Intelligent control for autonomous systems, IEEE Spectr., 32, 55, 10.1109/6.387144 Peruzzini, 2017, A framework to design a human-centred adaptive manufacturing system for aging workers, Adv. Eng. Inf., 43, 330, 10.1016/j.aei.2017.02.003 Petersen, 2016, 101 Preuveneers, 2018, Robust digital twin compositions for industry 4.0 smart manufacturing systems, 69 Qi, 2018, Digital twin and big data towards smart manufacturing and industry 4.0: 360 degree comparison, IEEE Access, 6, 3585, 10.1109/ACCESS.2018.2793265 Qu, 2016, IoT-based real-time production logistics synchronization system under smart cloud manufacturing, Int. J. Adv. Manuf. Technol., 84, 147, 10.1007/s00170-015-7220-1 Radziwon, 2014, The smart factory: exploring adaptive and flexible manufacturing solutions, Procedia Eng., 69, 1184, 10.1016/j.proeng.2014.03.108 Rasheed, 2019, 1 Rassolkin, 2019, Digital twin for propulsion drive of autonomous electric vehicle Reifsnider, 2013 Ríos, 2015, Product avatar as digital counterpart of a physical individual product: literature review and implications in an aircraft, Adv. Transdiscipl. Eng., 657 Rosen, 2015, About the importance of autonomy and digital twins for the future of manufacturing, IFAC-Papers On Line, 48, 567, 10.1016/j.ifacol.2015.06.141 Rosenberger, 2018, Context-awareness in industrial applications: definition, classification and use case, Procedia CIRP, 72, 1172, 10.1016/j.procir.2018.03.242 Sancarlos, 2021, From ROM of electrochemistry to AI-based battery digital and hybrid twin, Arch. Comput. Methods Eng., 28, 979, 10.1007/s11831-020-09404-6 Sanderson, 2015, Advanced manufacturing: an industrial application for collective adaptive systems, Proc. - 2015 IEEE 9th Int. Conf. Self-Adaptive Self-Organizing Syst. Work. SASOW 2015, 10.1109/SASOW.2015.15 Saracco, 2019, Digital Twins: bridging physical space and cyberspace, Computer (Long. Beach. Calif)., 52, 58 Schaumeier, 2012, A tripartite analytic framework for characterising awareness and self-awareness in autonomic systems research, 157 Schirner, 2013, The future of human-in-the-loop cyber-physical systems, Computer (Long. Beach. Calif)., 46, 36 Schleich, 2017, Shaping the digital twin for design and production engineering, CIRP Ann. - Manuf. Technol., 66, 141, 10.1016/j.cirp.2017.04.040 Scholz-Reiter, 2004, Autonomous logistic processes: New demands and first approaches, Proc. 37th CIRP Int. Semin. Manuf. Syst., 357 Scholz-Reiter, 2008, A survey of autonomous control algorithms by means of adapted vehicle routing problems, 1 B. Scholz-Reiter, M. Freitag, C. de Beer, T. Jagalski, Modelling and analysis of autonomous shop floor control, Sfb637.Uni-Bremen.De. (n.d.). http://www.sfb637.uni-bremen.de/fileadmin/SFB_Files/PDF_Download/SFB637-A5a-Ib-05-01.pdf (Accessed 10 July 2019). Schuldt, 2011, The interaction effort in autonomous logistics processes: potential and limitations for cooperation, 77 Shani, 2017, Ontology mediation to rule them all: managing the plurality in product service systems, 11th Annu. IEEE Int. Syst. Conf. SysCon 2017 - Proc., 10.1109/SYSCON.2017.7934810 Shaſto, 2012, A modeling, simulation, information technology & processing roadmap, Natl. Aeronaut. Sp. Adm., 1 Stark, 2019, Digital Twin, Int. Acad. Prod. Eng. CIRP Encycl. Prod. Eng. Steiner, 2008, 176 Talukdar, 1998, Asynchronous teams: cooperation schemes for autonomous agents, J. Heuristics., 4, 295, 10.1023/A:1009669824615 Tantik, 2017, Potentials of the asset administration shell of industrie 4.0 for service-oriented business models, Procedia CIRP, 363, 10.1016/j.procir.2017.03.009 Tao, 2014, IoT-based intelligent perception and access of manufacturing resource toward cloud manufacturing, IEEE Trans. Ind. Informatics, 10, 1547, 10.1109/TII.2014.2306397 Tao, 2019, Digital twin in industry: state-of-the-art, IEEE Trans. Ind. Inform., 15, 2405, 10.1109/TII.2018.2873186 Tao, 2019, Digital Twins and cyber–physical systems toward smart manufacturing and industry 4.0: correlation and comparison, Engineering, 5, 653, 10.1016/j.eng.2019.01.014 Tennenhouse, 2000, Proactive computing, Commun. ACM, 43, 43, 10.1145/332833.332837 Tuegel, 2012 E. Tuegel, A. Ingraffea, … T.E.-I.J. of, undefined 2011, Reengineering aircraft structural life prediction using a digital twin, Hindawi.Com. (n.d.). https://www.hindawi.com/journals/ijae/2011/154798/abs/ (Accessed 29 October 2019). Tzanis, 2020, A hybrid cyber physical digital twin approach for smart grid fault prediction, 393 Van Brussel, 2014, Holonic manufacturing systems, 654 C. Wagner, J. Grothoff, U. Epple, … R.D.-2017 22nd I., undefined 2017, The role of the Industry 4.0 asset administration shell and the digital twin during the life cycle of a plant, Ieeexplore.Ieee.Org. (n.d.), https://ieeexplore.ieee.org/abstract/document/8247583/ (Accessed 16 December 2019). Wang, 2016, Combined strength of holons, agents and function blocks in cyber-physical systems, Int. J. Ind. Manuf. Syst. Eng., 40, 25, 10.1016/j.jmsy.2016.05.002 Wang, 2018, Epistemic uncertainty-based model validation via interval propagation and parameter calibration, Comput. Methods Appl. Mech. Eng., 342, 161, 10.1016/j.cma.2018.08.001 Wang, 2019, Digital Twin for rotating machinery fault diagnosis in smart manufacturing, Int. J. Prod. Res., 57, 3920, 10.1080/00207543.2018.1552032 Wieland, 2010, Using context-aware workflows for failure management in a smart factory, UBICOMM 2010 - 4th Int. Conf. Mob. Ubiquitous Comput. Syst. Serv. Technol. Windt, 2010, A classification pattern for autonomous control methods in logistics, Logist. Res., 2, 109, 10.1007/s12159-010-0030-9 Wuest, 2013, 675 Zaccaria, 2018, Fleet monitoring and diagnostics framework based on digital twin of aero-engines, Proc. ASME Turbo Expo, American Society of Mechanical Engineers (ASME) Zhang, 2017, A Digital Twin-based approach for designing and multi-objective optimization of hollow glass production line, IEEE Access, 5, 26901, 10.1109/ACCESS.2017.2766453 Zhang, 2019 Zheng, 2020, A generic tri-model-based approach for product-level digital twin development in a smart manufacturing environment, Robot. Comput. Manuf., 64, 101958, 10.1016/j.rcim.2020.101958