A six-layer architecture for the digital twin: a manufacturing case study implementation

Industry 4.0, cyber-physical production systems (CPPS) and the Internet of Things (IoT) are current focusses in automation and data exchange in manufacturing, arising from the rapid increase in capabilities in information and communication technologies and the ubiquitous internet. A key enabler for...

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Veröffentlicht in:	Journal of intelligent manufacturing Jg. 31; H. 6; S. 1383 - 1402
Hauptverfasser:	Redelinghuys, A. J. H., Basson, A. H., Kruger, K.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.08.2020 Springer Nature B.V
Schlagworte:	Advanced manufacturing technologies Business and Management Control Data exchange Digital twins Horizontal integration Industrial applications Industry 4.0 Internet of Things Machines Manufacturing Mechatronics Processes Production Robotics Cyber physical systems (CPS) Industry 4.0 OPC Digital twin Tecnomatix Internet of things (IoT)
ISSN:	0956-5515, 1572-8145
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Abstract	Industry 4.0, cyber-physical production systems (CPPS) and the Internet of Things (IoT) are current focusses in automation and data exchange in manufacturing, arising from the rapid increase in capabilities in information and communication technologies and the ubiquitous internet. A key enabler for the advances promised by CPPSs is the concept of a digital twin , which is the virtual representation of a real-world entity, or the physical twin . An important step towards the success of Industry 4.0 is the establishment of practical reference architectures. This paper presents an architecture for such a digital twin, which enables the exchange of data and information between a remote emulation or simulation and the physical twin. The architecture comprises different layers, including a local data layer, an IoT Gateway layer, cloud-based databases and a layer containing emulations and simulations. The architecture can be implemented in new and legacy production facilities, with a minimal disruption of current installations. This architecture provides a service-based and real-time enabled infrastructure for vertical and horizontal integration. To evaluate the architecture, it was implemented for a small, but typical, physical manufacturing system component.
AbstractList	Industry 4.0, cyber-physical production systems (CPPS) and the Internet of Things (IoT) are current focusses in automation and data exchange in manufacturing, arising from the rapid increase in capabilities in information and communication technologies and the ubiquitous internet. A key enabler for the advances promised by CPPSs is the concept of a digital twin, which is the virtual representation of a real-world entity, or the physical twin. An important step towards the success of Industry 4.0 is the establishment of practical reference architectures. This paper presents an architecture for such a digital twin, which enables the exchange of data and information between a remote emulation or simulation and the physical twin. The architecture comprises different layers, including a local data layer, an IoT Gateway layer, cloud-based databases and a layer containing emulations and simulations. The architecture can be implemented in new and legacy production facilities, with a minimal disruption of current installations. This architecture provides a service-based and real-time enabled infrastructure for vertical and horizontal integration. To evaluate the architecture, it was implemented for a small, but typical, physical manufacturing system component. Industry 4.0, cyber-physical production systems (CPPS) and the Internet of Things (IoT) are current focusses in automation and data exchange in manufacturing, arising from the rapid increase in capabilities in information and communication technologies and the ubiquitous internet. A key enabler for the advances promised by CPPSs is the concept of a digital twin , which is the virtual representation of a real-world entity, or the physical twin . An important step towards the success of Industry 4.0 is the establishment of practical reference architectures. This paper presents an architecture for such a digital twin, which enables the exchange of data and information between a remote emulation or simulation and the physical twin. The architecture comprises different layers, including a local data layer, an IoT Gateway layer, cloud-based databases and a layer containing emulations and simulations. The architecture can be implemented in new and legacy production facilities, with a minimal disruption of current installations. This architecture provides a service-based and real-time enabled infrastructure for vertical and horizontal integration. To evaluate the architecture, it was implemented for a small, but typical, physical manufacturing system component.
Author	Kruger, K. Redelinghuys, A. J. H. Basson, A. H.
Author_xml	– sequence: 1 givenname: A. J. H. surname: Redelinghuys fullname: Redelinghuys, A. J. H. organization: Department of Mechanical and Mechatronic Engineering, Stellenbosch University – sequence: 2 givenname: A. H. surname: Basson fullname: Basson, A. H. organization: Department of Mechanical and Mechatronic Engineering, Stellenbosch University – sequence: 3 givenname: K. orcidid: 0000-0003-0932-2850 surname: Kruger fullname: Kruger, K. email: kkruger@sun.ac.za organization: Department of Mechanical and Mechatronic Engineering, Stellenbosch University
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Keywords	Cyber physical systems (CPS) Industry 4.0 OPC Digital twin Tecnomatix Internet of things (IoT)
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MorganJO’DonnellGECyber physical process monitoring systemsJournal of Intelligent Manufacturing20182961317132810.1007/s10845-015-1180-z Cearley, D. (2016). Gartner’s top 10 strategic technology trends for 2017. [Online]. Available: https://www.forbes.com/sites/gartnergroup/2016/10/26/gartners-top-10-strategic-technology-trends-for-2017/#629bc186b336. Retrieved November 27, 2017. H2020 - MAYA Project. (2019). Multi-disciplinArY integrated simulAtion and forecasting tools, empowered by digital continuity and continuous real-world synchronization, towards reduced time to production and optimization. [Online]. Available: http://maya-euproject.com/index.php/project. Retrieved July 19, 2019. BahetiRGillHCyber-physical systemsThe Impact of Control Technology2011121161166 LeeEAThe past, present and future of cyber-physical systems: A focus on modelsSensors (Basel)20151534837486910.3390/s150304837 Feuer, Z. & Weissman, Z. (2017). The value of the digital twin. [Online]. Available: https://community.plm.automation.siemens.com/t5/Digital-Transformations/The-value-of-the-digital-twin/ba-p/385812. Retrieved July 05, 2017. TaoFChengJQiQZhangMZhangHSuiFDigital twin-driven product design, manufacturing and service with big dataInternational Journal of Advanced Manufacturing Technology2018949–123563357610.1007/s00170-017-0233-1 Hoppe, S. (2017). There is no Industrie 4.0 without OPC UA. [Online]. Available: https://opcconnect.opcfoundation.org/2017/06/there-is-no-industrie-4-0-without-opc-ua/. Retrieved October 03, 2017. Martin, J. (2017). The value of automation and power of the digital twin. [Online]. Available: https://newsignature.com/articles/value-automation-power-digital-twin/. Retrieved November 27, 2017. Borangiu, T., Oltean, E., Răileanu, S., Anton, F., Anton, S. & Iacob, I. (2020). Embedded digital twin for ARTI-type control of semi-continuous production processes. In Service oriented, holonic and multi-agent manufacturing systems for industry of the future. SOHOMA 2019. studies in computational intelligence (vol. 853, pp. 113–133). Springer, Cham. Salvador PalauADhadaMHParlikadAKMulti-agent system architectures for collaborative prognosticsJournal of Intelligent Manufacturing20193082999301310.1007/s10845-019-01478-9 National Institute of Standards and TechnologyFoundations for innovation in cyber-physical systems2013National Institute of Standards and TechnologyWorkshop Report Vachalek, J., Bartalsky, L., Rovny, O., Sismisova, D., Morhac, M. & Loksik, M. (2017). The digital twin of an industrial production line within the industry 4.0 concept. In Proceedings of the 2017 21st international conference on process control, PC 2017 (pp. 258–262). LiuYPengYWangBYaoSLiuZReview on cyber-physical systemsIEEE/CAA Journal of Automatica Sinica201741274010.1109/JAS.2017.7510349 Oracle. (2017). Digital twins for IoT applications: A comprehensive approach to implementing IoT digital twins (White Paper). Redwood Shores. Siemens. (2014). Plant Simulation. [Online]. Available: https://www.plm.automation.siemens.com/en/products/tecnomatix/manufacturing-simulation/material-flow/plant-simulation.shtml#lightview%26url=/en_us/Images/7541_tcm1023-4957.pdf%26title=TecnomatixPlantSimulation%26description = Simulate,visualize,analyze. Retrieved October 05, 2017. Marr, B. (2017). What is digital twin technology—And why is it so important? [Online]. Available: https://www.forbes.com/sites/bernardmarr/2017/03/06/what-is-digital-twin-technology-and-why-is-it-so-important/#26203f1c2e2a. Retrieved January 22, 2018. Shafto, M., Conroy, M., Doyle, R. & Glaessgen, E. (2010). DRAFT modeling, simulation, information Technology & Processing Roadmap. Technology Area. Baur, C. & Wee, D. (2015). Manufacturing’s next act. [Online]. Available: http://www.mckinsey.com/business-functions/operations/our-insights/manufacturings-next-act. Retrieved July 05, 2017. Lee, E.A. & Seshia, S.A. (2017). Introduction to embedded systems—A cyber-physical systems approach. 2nd ed. RedelinghuysAJHBassonAHKrugerKBorangiuTTrentesauxDThomasACavalieriSA six-layer digital twin architecture for a manufacturing cellService orientation in holonic and multi-agent manufacturing. SOHOMA 2018 studies in computational intelligence2019ChamSpringer412423 M.A.C. Solutions. (2017). KEPServerEX V6 OPC Server. [Online]. Available: https://www.mac-solutions.net/en/products/industrial-data-comms/opc-communications-suite/item/157-kepserverex-v6-opc-server. Retrieved November 21, 2017. CavalieriSChiacchioFAnalysis of OPC UA performancesComputer Standards and Interfaces201336116517710.1016/j.csi.2013.06.004 GrievesMDigital twin: Manufacturing excellence through virtual factory replication2014MelbourneWhite Paper KritzingerWKarnerMTraarGHenjesJSihnWDigital Twin in manufacturing: A categorical literature review and classificationIFAC-PapersOnLine201851111016102210.1016/j.ifacol.2018.08.474 Soldatos, J., Lazaro, O. & Cavadini, F. (2019). The digital shopfloor—Industrial automation in the Industry 4.0 Era: Performance analysis and applications. NakutisZDeksnysVJaruseviciusIDambrauskasVCincikasGKriauceliunasARound-trip delay estimation in OPC UA ServerClient communication channelElektronika ir Elektrotechnika2016226808410.5755/j01.eie.22.6.17229 LeeJBagheriBKaoH-AA cyber-physical systems architecture for Industry 4.0-based manufacturing systemsManufacturing Letters20153182310.1016/j.mfglet.2014.12.001 Oztemel, E. & Gursev, S. (2018). Literature review of Industry 4.0 and related technologies. Journal of Intelligent Manufacturing. 29:1–56. OPC Foundation. (2015). Update for IEC 62541 (OPC UA) Published. [Online]. Available: https://opcfoundation.org/news/opc-foundation-news/update-iec-62541-opc-ua-published/. Retrieved September 28, 2017. RedelinghuysAJHKrugerKBassonAHBorangiuTTrentesauxDLeitãoPGiret BogginoABottiVA six-layer architecture for digital twins with aggregationService oriented Holonic and multi-agent manufacturing2020ChamSpringer17118210.1007/978-3-030-27477-1_13 Defuse Security. (2017). Salted Password Hashing - Doing it Right. [Online]. Available: https://crackstation.net/hashing-security.htm. Retrieved March 15, 2018. Bottani, E., Cammardella, A., Murino, T. & Vespoli, S. (2017). From the cyber-physical system to the digital twin: The process development for behaviour modelling of a cyber guided vehicle in M2M logic. In Proceedings of the summer school Francesco Turco (pp. 96–102). Manufacturing Industry Digital Innovation Hubs (MIDIH). (2018). Functional and Modular Architecture of MIDIH CPS/IOT System (Public Version). [Online]. Available: http://midih.eu/documents/MIDIH Reference architecture.pdf. Retrieved July 19, 2019. PTC Inc. (2017). ClientAce user manual. [Online]. Available: https://www.kepware.com/en-us/products/clientace/documents/clientace-manual.pdf. Retrieved March 08, 2018. RovereDPedrazzoliPdal MasoGAlgeMCiavottaMSoldatosJLazaroOCavadiniFA Centralized Support Infrastructure (CSI) to Manage CPS Digital Twin, towards the Synchronization between CPS Deployed on the Shopfloor and Their Digital RepresentationThe digital shopfloor—Industrial automation in the industry 4.0 Era: performance analysis and applications2019DenmarkRiver Publishers317335 SchroederGNSteinmetzCPereiraCEEspindolaDBDigital twin data modeling with automationML and a communication methodology for data exchangeIFAC-PapersOnLine20164930121710.1016/j.ifacol.2016.11.115 PatelKTChotaiNPDocumentation and records: Harmonized GMP requirementsJournal of Young Pharmacists20113213815010.4103/0975-1483.80303 RăileanuSBorangiuTIvănescuNMorariuOAntonTBorangiuTTrentesauxDLeitãoPGiret BogginoABottiVIntegrating the digital twin of a shop floor conveyor in the manufacturing control systemService oriented, holonic and multi-agent manufacturing systems for industry of the future. SOHOMA 2019. studies in computational intelligence2020ChamSpringer134145 SchleichBAnwerNMathieuLWartzackSShaping the digital twin for design and production engineeringCIRP Annals—Manufacturing Technology.201766114114410.1016/j.cirp.2017.04.040 TaoFQiQWangLNeeAYCDigital twins and cyber–physical systems toward smart manufacturing and industry 4.0: Correlation and comparisonEngineering.20195465366110.1016/j.eng.2019.01.014 Bagheri, B. & Lee, J. (2015). Big future for cyber-physical manufacturing systems. [Online]. Available: http://www.designworldonline.com/big-future-for-cyber-physical-manufacturing-systems/. Retrieved July 05, 2017. Cavalieri, S. & Cutuli, G. (2010). Performance evaluation of OPC UA. In 2010 IEEE 15th conference on emerging technologies & factory automation (ETFA 2010) (pp. 1–8). Kagermann, H., Helbig, J., Hellinger, A. & Wahlster, W. (2013). Recommendations for implementing the strategic initiative INDUSTRIE 4.0: Securing the future of German manufacturing industry; final report of the Industrie 4.0 Working Group. 1516_CR14 1516_CR15 KT Patel (1516_CR33) 2011; 3 1516_CR37 AJH Redelinghuys (1516_CR36) 2019 1516_CR19 S Răileanu (1516_CR35) 2020 R Baheti (1516_CR2) 2011; 12 W Kritzinger (1516_CR16) 2018; 51 1516_CR30 1516_CR31 1516_CR10 1516_CR32 1516_CR12 1516_CR34 1516_CR13 L Monostori (1516_CR26) 2016; 65 Y Liu (1516_CR21) 2017; 4 F Tao (1516_CR46) 2018; 94 D Rovere (1516_CR39) 2019 P Leitão (1516_CR20) 2016; 81 M Grieves (1516_CR11) 2014 S Cavalieri (1516_CR6) 2013; 36 1516_CR25 1516_CR48 1516_CR3 1516_CR4 1516_CR1 1516_CR43 1516_CR22 1516_CR44 1516_CR23 1516_CR45 1516_CR24 F Tao (1516_CR47) 2019; 5 1516_CR9 GN Schroeder (1516_CR42) 2016; 49 Z Nakutis (1516_CR28) 2016; 22 1516_CR7 J Morgan (1516_CR27) 2018; 29 B Schleich (1516_CR41) 2017; 66 1516_CR8 AJH Redelinghuys (1516_CR38) 2020 1516_CR5 A Salvador Palau (1516_CR40) 2019; 30 EA Lee (1516_CR17) 2015; 15 J Lee (1516_CR18) 2015; 3 National Institute of Standards and Technology (1516_CR29) 2013
References_xml	– reference: BahetiRGillHCyber-physical systemsThe Impact of Control Technology2011121161166 – reference: Grieves, M. (2015). How A “Digital Twin” Can Warrant Products Are Built As Designed. [Online]. Available: https://www.mbtmag.com/article/2015/01/how-‘digital-twin’-can-warrant-products-are-built-designed. Retrieved July 05, 2017. – reference: Defuse Security. (2017). Salted Password Hashing - Doing it Right. [Online]. Available: https://crackstation.net/hashing-security.htm. Retrieved March 15, 2018. – reference: GrievesMDigital twin: Manufacturing excellence through virtual factory replication2014MelbourneWhite Paper – reference: PatelKTChotaiNPDocumentation and records: Harmonized GMP requirementsJournal of Young Pharmacists20113213815010.4103/0975-1483.80303 – reference: NakutisZDeksnysVJaruseviciusIDambrauskasVCincikasGKriauceliunasARound-trip delay estimation in OPC UA ServerClient communication channelElektronika ir Elektrotechnika2016226808410.5755/j01.eie.22.6.17229 – reference: Baur, C. & Wee, D. (2015). Manufacturing’s next act. [Online]. Available: http://www.mckinsey.com/business-functions/operations/our-insights/manufacturings-next-act. Retrieved July 05, 2017. – reference: Cearley, D. (2016). Gartner’s top 10 strategic technology trends for 2017. [Online]. Available: https://www.forbes.com/sites/gartnergroup/2016/10/26/gartners-top-10-strategic-technology-trends-for-2017/#629bc186b336. Retrieved November 27, 2017. – reference: LeeEAThe past, present and future of cyber-physical systems: A focus on modelsSensors (Basel)20151534837486910.3390/s150304837 – reference: Kagermann, H., Helbig, J., Hellinger, A. & Wahlster, W. (2013). Recommendations for implementing the strategic initiative INDUSTRIE 4.0: Securing the future of German manufacturing industry; final report of the Industrie 4.0 Working Group. – reference: Marr, B. (2017). What is digital twin technology—And why is it so important? [Online]. Available: https://www.forbes.com/sites/bernardmarr/2017/03/06/what-is-digital-twin-technology-and-why-is-it-so-important/#26203f1c2e2a. Retrieved January 22, 2018. – reference: Vachalek, J., Bartalsky, L., Rovny, O., Sismisova, D., Morhac, M. & Loksik, M. (2017). The digital twin of an industrial production line within the industry 4.0 concept. In Proceedings of the 2017 21st international conference on process control, PC 2017 (pp. 258–262). – reference: Martin, J. (2017). The value of automation and power of the digital twin. [Online]. Available: https://newsignature.com/articles/value-automation-power-digital-twin/. Retrieved November 27, 2017. – reference: TaoFQiQWangLNeeAYCDigital twins and cyber–physical systems toward smart manufacturing and industry 4.0: Correlation and comparisonEngineering.20195465366110.1016/j.eng.2019.01.014 – reference: RovereDPedrazzoliPdal MasoGAlgeMCiavottaMSoldatosJLazaroOCavadiniFA Centralized Support Infrastructure (CSI) to Manage CPS Digital Twin, towards the Synchronization between CPS Deployed on the Shopfloor and Their Digital RepresentationThe digital shopfloor—Industrial automation in the industry 4.0 Era: performance analysis and applications2019DenmarkRiver Publishers317335 – reference: Feuer, Z. & Weissman, Z. (2017). The value of the digital twin. [Online]. Available: https://community.plm.automation.siemens.com/t5/Digital-Transformations/The-value-of-the-digital-twin/ba-p/385812. Retrieved July 05, 2017. – reference: Redelinghuys, A.J.H., Basson, A.H. & Kruger, K. 2019b. Cybersecurity Considerations for Industrie 4.0. In D. Dimitrov, D. Hagedorn-Hansen, & K. von Leipzig (Eds.) International conference on competitive manufacturing (COMA 19). Knowledge valorisation in the age of digitalization (pp. 266–271). Stellenbosch. – reference: RedelinghuysAJHKrugerKBassonAHBorangiuTTrentesauxDLeitãoPGiret BogginoABottiVA six-layer architecture for digital twins with aggregationService oriented Holonic and multi-agent manufacturing2020ChamSpringer17118210.1007/978-3-030-27477-1_13 – reference: SchroederGNSteinmetzCPereiraCEEspindolaDBDigital twin data modeling with automationML and a communication methodology for data exchangeIFAC-PapersOnLine20164930121710.1016/j.ifacol.2016.11.115 – reference: Lee, E.A. & Seshia, S.A. (2017). Introduction to embedded systems—A cyber-physical systems approach. 2nd ed. – reference: National Institute of Standards and TechnologyFoundations for innovation in cyber-physical systems2013National Institute of Standards and TechnologyWorkshop Report – reference: PTC Inc. (2017). ClientAce user manual. [Online]. Available: https://www.kepware.com/en-us/products/clientace/documents/clientace-manual.pdf. Retrieved March 08, 2018. – reference: SchleichBAnwerNMathieuLWartzackSShaping the digital twin for design and production engineeringCIRP Annals—Manufacturing Technology.201766114114410.1016/j.cirp.2017.04.040 – reference: TaoFChengJQiQZhangMZhangHSuiFDigital twin-driven product design, manufacturing and service with big dataInternational Journal of Advanced Manufacturing Technology2018949–123563357610.1007/s00170-017-0233-1 – reference: Salvador PalauADhadaMHParlikadAKMulti-agent system architectures for collaborative prognosticsJournal of Intelligent Manufacturing20193082999301310.1007/s10845-019-01478-9 – reference: Soldatos, J., Lazaro, O. & Cavadini, F. (2019). The digital shopfloor—Industrial automation in the Industry 4.0 Era: Performance analysis and applications. – reference: Bagheri, B. & Lee, J. (2015). Big future for cyber-physical manufacturing systems. [Online]. Available: http://www.designworldonline.com/big-future-for-cyber-physical-manufacturing-systems/. Retrieved July 05, 2017. – reference: RăileanuSBorangiuTIvănescuNMorariuOAntonTBorangiuTTrentesauxDLeitãoPGiret BogginoABottiVIntegrating the digital twin of a shop floor conveyor in the manufacturing control systemService oriented, holonic and multi-agent manufacturing systems for industry of the future. SOHOMA 2019. studies in computational intelligence2020ChamSpringer134145 – reference: MorganJO’DonnellGECyber physical process monitoring systemsJournal of Intelligent Manufacturing20182961317132810.1007/s10845-015-1180-z – reference: OPC Foundation. (2015). Update for IEC 62541 (OPC UA) Published. [Online]. Available: https://opcfoundation.org/news/opc-foundation-news/update-iec-62541-opc-ua-published/. Retrieved September 28, 2017. – reference: MonostoriLKádárBBauernhanslTKondohSKumaraSReinhartGSauerOSchuhGSihnWUedaKCyber-physical systems in manufacturingCIRP Annals—Manufacturing Technology201665262164110.1016/j.cirp.2016.06.005 – reference: Borangiu, T., Oltean, E., Răileanu, S., Anton, F., Anton, S. & Iacob, I. (2020). Embedded digital twin for ARTI-type control of semi-continuous production processes. In Service oriented, holonic and multi-agent manufacturing systems for industry of the future. SOHOMA 2019. studies in computational intelligence (vol. 853, pp. 113–133). Springer, Cham. – reference: Bottani, E., Cammardella, A., Murino, T. & Vespoli, S. (2017). From the cyber-physical system to the digital twin: The process development for behaviour modelling of a cyber guided vehicle in M2M logic. In Proceedings of the summer school Francesco Turco (pp. 96–102). – reference: Oztemel, E. & Gursev, S. (2018). Literature review of Industry 4.0 and related technologies. Journal of Intelligent Manufacturing. 29:1–56. – reference: LeitãoPColomboAWKarnouskosSIndustrial automation based on cyber-physical systems technologies: Prototype implementations and challengesComputers in Industry201681112510.1016/j.compind.2015.08.004 – reference: Cavalieri, S. & Cutuli, G. (2010). Performance evaluation of OPC UA. In 2010 IEEE 15th conference on emerging technologies & factory automation (ETFA 2010) (pp. 1–8). – reference: Manufacturing Industry Digital Innovation Hubs (MIDIH). (2018). Functional and Modular Architecture of MIDIH CPS/IOT System (Public Version). [Online]. Available: http://midih.eu/documents/MIDIH Reference architecture.pdf. Retrieved July 19, 2019. – reference: KritzingerWKarnerMTraarGHenjesJSihnWDigital Twin in manufacturing: A categorical literature review and classificationIFAC-PapersOnLine201851111016102210.1016/j.ifacol.2018.08.474 – reference: Siemens. (2014). Plant Simulation. [Online]. Available: https://www.plm.automation.siemens.com/en/products/tecnomatix/manufacturing-simulation/material-flow/plant-simulation.shtml#lightview%26url=/en_us/Images/7541_tcm1023-4957.pdf%26title=TecnomatixPlantSimulation%26description = Simulate,visualize,analyze. Retrieved October 05, 2017. – reference: Hoppe, S. (2017). There is no Industrie 4.0 without OPC UA. [Online]. Available: https://opcconnect.opcfoundation.org/2017/06/there-is-no-industrie-4-0-without-opc-ua/. Retrieved October 03, 2017. – reference: RedelinghuysAJHBassonAHKrugerKBorangiuTTrentesauxDThomasACavalieriSA six-layer digital twin architecture for a manufacturing cellService orientation in holonic and multi-agent manufacturing. SOHOMA 2018 studies in computational intelligence2019ChamSpringer412423 – reference: CavalieriSChiacchioFAnalysis of OPC UA performancesComputer Standards and Interfaces201336116517710.1016/j.csi.2013.06.004 – reference: LiuYPengYWangBYaoSLiuZReview on cyber-physical systemsIEEE/CAA Journal of Automatica Sinica201741274010.1109/JAS.2017.7510349 – reference: M.A.C. Solutions. (2017). KEPServerEX V6 OPC Server. [Online]. Available: https://www.mac-solutions.net/en/products/industrial-data-comms/opc-communications-suite/item/157-kepserverex-v6-opc-server. Retrieved November 21, 2017. – reference: Shafto, M., Conroy, M., Doyle, R. & Glaessgen, E. (2010). DRAFT modeling, simulation, information Technology & Processing Roadmap. Technology Area. – reference: H2020 - MAYA Project. (2019). Multi-disciplinArY integrated simulAtion and forecasting tools, empowered by digital continuity and continuous real-world synchronization, towards reduced time to production and optimization. [Online]. Available: http://maya-euproject.com/index.php/project. Retrieved July 19, 2019. – reference: LeeJBagheriBKaoH-AA cyber-physical systems architecture for Industry 4.0-based manufacturing systemsManufacturing Letters20153182310.1016/j.mfglet.2014.12.001 – reference: Oracle. (2017). Digital twins for IoT applications: A comprehensive approach to implementing IoT digital twins (White Paper). Redwood Shores. – ident: 1516_CR3 – ident: 1516_CR5 – ident: 1516_CR22 – start-page: 134 volume-title: Service oriented, holonic and multi-agent manufacturing systems for industry of the future. 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Snippet	Industry 4.0, cyber-physical production systems (CPPS) and the Internet of Things (IoT) are current focusses in automation and data exchange in manufacturing,...
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StartPage	1383
SubjectTerms	Advanced manufacturing technologies Business and Management Control Data exchange Digital twins Horizontal integration Industrial applications Industry 4.0 Internet of Things Machines Manufacturing Mechatronics Processes Production Robotics
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Title	A six-layer architecture for the digital twin: a manufacturing case study implementation
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Volume	31
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