An open source approach to the design and implementation of Digital Twins for Smart Manufacturing

References

• Afify, Y., I. F. Moawad, N. Badr, and M. Tolba 2013. “A Semantic-Based Software-As-A-Service (SAAS) Discovery and Selection System.” In Proceedings of the 8th IEEE International Conference on Computer Engineering & Systems (IC-CES), Cairo, Egypt, pp. 57–63. doi:10.1177/1753193412446112.
   Google Scholar
• Aggarwal, S., S. Phadke, and M. Bhandarkar 2010. “Characterization of Hadoop Jobs Using Unsupervised Learning.” In Proc. of the Cloud Computing Technology and Science (CloudCom), 748–753. doi: 10.1109/CloudCom.2010.20.
   Google Scholar
• Alsafi, Y., and V. Vyatkin. 2010. “Ontology-Based Reconfiguration Agent for Intelligent Mechatronic Systems in Flexible Manufacturing.” In Robotics and Computer-Integrated Manufacturing 26 (4): 381–391. doi:10.1016/j.rcim.2009.12.001.
   Web of Science ®Google Scholar
• Ameri, F., C. Urbanovsky, and C. McArthur 2012. “A Systematic Approach to Developing Ontologies for Manufacturing Service Modeling.” In Proc. of the 7th Inter. Conf. on Formal Ontology in Information Systems (FOIS). doi:10.1094/PDIS-11-11-0999-PDN.
   Google Scholar
• Ashbrook, D., and T. Starner 2002. “Learning Significant Locations and Predicting User Movement with GPS.” In Proc. of the IEEE 6th Inter. Symposium on Wearable Computers (ISWC 2002), doi: 10.1109/ISWC.2002.1167224.
   Google Scholar
• Ashbrook, D., and T. Starner. 2003. “Using GPS to Learn Significant Locations and Predict Movement across Multiple Users.” Personal and Ubiquitous Computing 7: 275–286. doi:10.1007/s00779-003-0240-0.
   Web of Science ®Google Scholar
• Avancha, S., C. Patel, and A. Joshi 2004. “Ontology-Driven Adaptive Sensor Networks. Mobile and Ubiquitous Systems: Networking and Services.” In Proceedings of the 1st Annual International Conference on MOBIQUITOUS 2004, Boston, MA, USA, pp. 194–202.
   Google Scholar
• Baheti, R., and H. Gill. 2011. “Cyber-Physical Systems.” The Impact of Control Technology 12: 161–166.
   Google Scholar
• Bahga, A., and V. K. Madisetti. 2011. “Synthetic Workload Generation for Cloud Computing Applications.” Journal of Software Engineering and Applications 4: 396–410. doi:10.4236/jsea.2011.47046.
   Google Scholar
• Berman, D. 2017. “InfluxDB Vs. Elasticsearch for Time Series Analysis.” https://logz.io/blog/influxdb-vs-elasticsearch/
   Google Scholar
• Boschert, S., and R. Rosen. 2016. “Digital Twin—The Simulation Aspect.” In Mechatronic Futures: Challenges and Solutions for Mechatronic Systems and Their Designers, edited by P. Hehenberger and D. Bradley, 9–74, Springer International Pub., Cham.
   Google Scholar
• Cai, M., W. Y. Zhang, and K. Zhang. 2001. “ManuHub: A Semantic Web System for Ontology-Based Service Management, Distributed Manufacturing Environments.” In IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans 41 (3): 574–582. doi:10.1109/TSMCA.2010.2076395.
   Google Scholar
• Chang, X., R. Rai, and J. Terpenny. 2010. “Development and Utilization of Ontologies in Design for Manufacturing.” Journal on Mechanical Design 132 (2): 021009–021009-12,1–12. doi:10.1115/1.4000697.
   Web of Science ®Google Scholar
• Chen, Y., A. Ganapathi, R. Griffith, and R. H. Katz 2010. “Analysis and Lessons from a Publicly Available Google Cluster Trace.” In Proceedings of the EECS Department, University of California, Berkeley.
   Google Scholar
• Choi, S. S., T. H. Yoon, and S. D. Noh. 2010. “XML-based Neutral File and PLM Integrator for PPR Information Exchange between Heterogeneous PLM Systems.” International Journal of Computer Integrated Manufacturing 23 (3): 216–228. doi:10.1080/09511920903443234.
   Web of Science ®Google Scholar
• Chungoora, N., R. I. Young, G. Gunendran, C. Palmer, Z. Usman, N. A. Anjum, A.-F. Cutting-Decelle, J. A. Harding, and K. Case. 2013. “A Model-Driven Ontology Approach for Manufacturing System Interoperability and Knowledge Sharing.” Journal on Computers in Industry 64 (4): 392–401. doi:10.1016/j.compind.2013.01.003.
   Web of Science ®Google Scholar
• Churilo, C. 2018. “InfluxDB Vs. Elasticsearch for Time Series Data & Metrics Benchmark.” https://bit.ly/2snLUN5
   Google Scholar
• Cimini, C., R. Pinto, and S. Cavalieri 2017. “The Business Transformation Towards Smart Manufacturing: A Literature Overview about Reference Models and Research Agenda.” In Proceedings of the International Federation of Automatic Control Conference (IFAC). 1452–1457. doi: 10.1016/j.ifacol.2017.08.2548.
   Google Scholar
• Damjanovic-Behrendt, V. 2018. “A Digital Twin Architecture for Security, Privacy and Safety”. ERCIM News No. 115, Special Issue “Digital Twins”. https://bit.ly/2CCU0Il
   Google Scholar
• Davis, J., T. Edgar, J. Porter, J. Bernaden, and M. Sarli. 2012. “Smart Manufacturing, Manufacturing Intelligence and Demand-Dynamic Performance.” Computers & Chemical Engineering 47: 145–156. doi:10.1016/j.compchemeng.2012.06.037.
   Web of Science ®Google Scholar
• Diep, D., C. Alexakos, and T. Wagner 2007. “An Ontology-Based Interoperability Framework for Distributed Manufacturing Control.” In Proceedings of the IEEE Conference on Emerging Technologies and Factory Automation (ETFA), Patras, Greece, 855–862. doi:10.1094/PDIS-91-4-0467B.
   Google Scholar
• Dobbelaere, P., and K. S. Esmaili 2017. “Kafka versus RabbitMQ: A Comparative Study of Two Industry Reference Publish/Subscribe Implementations: Industry Paper.” In Proceedings of the 11th ACM International Int. Conf. on Distributed and Event-based Systems (DEBS ‘17), 227–238. doi:10.2147/COPD.S130231.
   Google Scholar
• DZone. 2018. “DZone Guide to Open Source: Democratizing Development.” Accessed May 2018. https://bit.ly/2jLCN4V
   Google Scholar
• ECLIF. 2010. “Extended Common Logic Interchange Format (ECLIF) Reference.” In: Proprietary document supplied with the installation of the Highfleet Integrated Ontology Development Environment (IODE) Application.
   Google Scholar
• Esposito, C., A. Castiglione, and K.-K. R. Choo. 2016. “Challenges in Delivering Software in the Cloud as Microservices.” IEEE Cloud Computing 3 (5): 10–14. doi:10.1109/MCC.2016.105.
   Web of Science ®Google Scholar
• Fan, J., F. Han, and H. Liu. 2014. “Challenges of Big Data Analysis.” National Science Review 1 (2): 293–314. doi:10.1093/nsr/nwt032.
   PubMed Web of Science ®Google Scholar
• Freeman, H. 2016. “Streaming Analytics 101: The What, Why, and How.” http://www.dataversity.net/streaming-analytics-101/
   Google Scholar
• Gabor, T., L. Belzner, and M. Kiermeier 2016. “A Simulation-Based Architecture for Smart Cyber-Physical Systems.” In Proceedings of the 2016 IEEE International Conference on Autonomic Computing (ICAC), 2016:374–379. doi: 10.1109/ICAC.2016.29.
   Google Scholar
• Gandomi, A., and M. Haider. 2015. “Beyond the Hype: Big Data Concepts, Methods, and Analytics.” International Journal of Information Management 35 (2): 137–144. doi:10.1016/j.ijinfomgt.2014.10.007.
   Web of Science ®Google Scholar
• Garetti, M., and L. Fumagalli. 2012. “P-PSO Ontology for Manufacturing Systems.” INCOM 2012—Information Control in Manufacturing Conference 14 (1): 449–456. doi:10.3182/20120523-3-RO-2023.00222.
   Google Scholar
• Garetti, M., and L. Fumagalli 2012a. “Role of Ontologies in Open Automation of Manufacturing Systems.” In Proceedings of the 17th Summer School in Industrial Mechanical Plants, Venice, Italy.
   Google Scholar
• Garetti, M., L. Fumagalli, A. Lobov, and J. Martinez Lastra. 2013. “Open Automation of Manufacturing Systems through Integration of Ontology and Web Services.” In Proceedings of the 7th IFAC Conference on Manufacturing Modelling, Management, and Control. doi:10.3182/20130619-3-RU-3018.00169.
   Google Scholar
• Garetti, M., L. Fumagalli, and E. Negri. 2015. “Role of Ontologies for CPS Implementation in Manufacturing.” In Management and Production Engineering Review 6: 4. doi:10.1515/mper-2015-0033.
   Web of Science ®Google Scholar
• Geng, X., H. Arimura, and T. Uno 2012. “Pattern Mining from Trajectory GPS Data.” In Proceedings of the 2012 IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012, Fukuoka, Japan, pp.60–65.
   Google Scholar
• Giovannini, A., A. Aubry, H. Panetto, M. Dassisti, and H. E. Haouzi. 2012. “Ontology-Based System for Supporting Manufacturing Sustainability.” Annual Reviews in Control 36 (2): 309–317. doi:10.1016/j.arcontrol.2012.09.012.
   Web of Science ®Google Scholar
• Grieves, M. 2014. “Digital Twin: Manufacturing Excellence through Virtual Factory Replication.” White paper. https://bit.ly/2slbtiR
   Google Scholar
• Grieves, M., and J. Vickers. 2017. “Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems.” In Transdisciplinary Perspectives on Complex Systems: New Findings and Approaches, edited by F.-J. Kahlen, S. Flumerfelt, and A. Alves, 85–113. Springer International Pub. doi:10.1007/978-3-319-38756-7_4.
   Google Scholar
• Haag, S., and R. Anderl. 2018. “Digital Twin - Proof of Concept.” Manufacturing Letters 15 (B): 64–66. doi:10.1016/j.mfglet.2018.02.00.
   Google Scholar
• Horváth, I., and B. Gerritsen. 2012. “Cyber-Physical System: Concepts, Technologies and Manifestation.” In Proceedings of the TMCE 2012 1: 1–16.
   Google Scholar
• Industrial Internet Consortium. 2017. “The Industrial Internet of Things.” Volume G1: Reference Architecture. https://bit.ly/2B1Lteg
   Google Scholar
• IoT Eclipse.org, 2017. “Open Source Software for Industry 4.0.” Accessed February 2019. https://bit.ly/2gIbVow
   Google Scholar
• Jazdi, N. 2014. “Cyber Physical Systems in the Context of Industry 4.0.” In Proceeding of the 2014 IEEE International Conference on Automation, Quality and Testing, Robotics. pp.1–4. doi: 10.1109/AQTR.2014.6857843.
   Google Scholar
• Kang, H. S., J. Y. Lee, S. Choi, H. Kim, J. H. Park, J. Y. Son, B. H. Kim, and S. D. Noh. 2016. “Smart Manufacturing: Past Research, Present Findings, and Future Directions.” International Journal of Precision Engineering and Manufacturing-Green Technologies 3: 111–128. doi:10.1007/s40684-016-0015-5.
   Web of Science ®Google Scholar
• Kiritsis, D. 2011. “Closed-Loop PLM for Intelligent Products in the Era of the Internet of Things.” Computer-Aided Design 43 (5): 479–501. doi:10.1016/j.cad.2010.03.002.
   Web of Science ®Google Scholar
• Kiritsis, D., S. Kadiri, A. Perdikakis, A. Milicic, D. Alexandrou, and K. Pardalis. 2013. “Design of Fundamental Ontology for Manufacturing Product Lifecycle Applications.” In Advances in Production Management Systems. Competitive Manufacturing for Innovative Products and Services. APMS 2012. IFIP Advances in Information and Communication Technology, edited by C. Emmanouilidis, M. Taisch, and D. Kiritsis. Vol. 397, pp. 376-382. Berlin, Heidelberg: Springer.
   Google Scholar
• Koren, Y., and M. Shpitalni. 2010. “Design of Reconfigurable Manufacturing Systems.” Journal of Manufacturing Systems 29 (4): 130–141. doi:10.1016/j.jmsy.2011.01.001.
   Web of Science ®Google Scholar
• Koren, Y., U. Heisel, F. Jovane, T. Moriwaki, G. Pritschow, A. G. Ulsoy, and H. Van Brussel. 1999. “Reconfigurable Manufacturing Systems.” Annals of the CIRP 48 (2): 527–540. doi:10.1016/S0007-8506(07)63232-6.
   Web of Science ®Google Scholar
• Kraft, E. 2016. “The Air Force Digital Thread/Digital Twin - Life Cycle Integration and Use of Computational and Experimental Knowledge.” In Proc. of the 54th AIAA Aerospace Sci. Meeting, AIAA SciTech Forum. doi: 10.2514/6.2016-0897.
   Google Scholar
• Kucera, R., M. Aanenson, and M. Benson, 2017. “The Augmented Digital Twin: Combining Physical and Virtual Data to Unlock the Value of IoT.” Exosite White paper. https://bit.ly/2sirAws
   Google Scholar
• Lee, E. A. 2008. “Cyber Physical Systems: Design Challenges.” In Proceedings of the 11th IEEE Intern. Symposium on Object and Component-Oriented Real-Time Distributed Computing, 363–369. doi: 10.1109/ISORC.2008.25.
   Google Scholar
• Lee, J., B. Bagheri, and H.-A. Kao. 2015. “A Cyber-Physical Systems Architecture for Industry 4.0-Based Manufacturing Systems.” Manufacturing Letters 3: 18–23. doi:10.1016/j.mfglet.2014.12.001.
   Google Scholar
• Lee, J., H.-A. Kao, and S. Yang. 2014. “Service Innovation and Smart Analytics for Industry 4.0 And Big Data Environment.” In Proceedings of CIRP 16: 3–8. Elsevier. doi:10.1016/j.procir.2014.02.001.
   Google Scholar
• Lemaignan, S., A. Siadat, D. Jean-Yves, and A. Semenenko 2006. “MASON: A Proposal for an Ontology of Manufacturing Domain.” IEEE Workshop on Distributed Intelligent Systems: Collective Intelligence and Its Applications (DIS 2006), Prague, Czech Republic, 195–200.
   Google Scholar
• Lewis, J., and M. Fowler 2014. “Microservices.” Accessed February 2019 https://martinfowler.com/articles/microservices.html
   Google Scholar
• Liao, Y., F. Deschamps, R. E. Loures, and P. F. Ramos. 2017. “Past, Present and Future of Industry 4.0—A Systematic Literature Review and Research Agenda Proposal.” International Journal of Production Research 55 (12): 3609–3629. doi:10.1080/00207543.2017.1308576.
   Web of Science ®Google Scholar
• Lin, S.-W., et al. 2017. “Architecture Alignment and Interoperability.” An Industrial Internet Consortium and Plattform Industrie 4.0 Joint Whitepaper. IIC:WHT:IN3: V1.0:PB:20171205
   Google Scholar
• Liu, L., X. Yao, L. Qin, and M. Zhang 2014. “Ontology-Based Service Matching in Cloud Computing.” In Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ- IEEE), pp.2544–2550. doi:10.1109/FUZZ-IEEE.2014.6891698.
   Google Scholar
• Lüder, A., L. Hundt, and A. Keibel 2010. “Description of Manufacturing Processes Using AutomationML.” In Proceedings of the 2010 IEEE Conference on Emerging Technologies and Factory Automation, 1–8. doi: 10.1109/ETFA.2010.5641346.
   Google Scholar
• MacDougall, W. 2014. “Industrie 4.0 Smart Manufacturing for the Future.” Mechanical & Electronic Technologies, Germany Trade & Invest (4) 40. Accessed February 2019. https://bit.ly/2RFdbW9
   Google Scholar
• McCool, M. 2017. “The Web of Things and Semantic Interoperability.” IETF1000. Accessed February 2019. https://bit.ly/2GisJ0M
   Google Scholar
• McLeod, I., H. Yu, and E. Mahdi. 2011. “Time Series Analysis with R.” Elsevier Handbook of Statistics 30. Available https://bit.ly/2L9J2uY
   Google Scholar
• Menzel, C., and M. Grüninger 2001. “A Formal Foundation for Process Modeling.” In Proceedings of the Second International Conference on Formal Ontologies in Information Systems, Welty and Smith (Eds.), 256–269.
   Google Scholar
• Mishra, A., J. Hellerstein, W. Cirne, and C. Das. 2010. “Towards Characterizing Cloud Backend Workloads: Insights from Google Compute Clusters.” In SIGMETRICS Performance Evaluation Review 37, Fukuoka, Japan. pp. 34–41. doi:10.1145/1773394.1773400.
   Google Scholar
• Mnih, V., H. Larochelle, and G. E. Hinton 2011. “Conditional Restricted Boltzmann Machines for Structured Output Prediction.” In Proceedings of the 27th Conference on Uncertainty in AI (UAI‘11), F. Cozman and A. Pfeffer (Eds.). AUAI Press, 514–522. doi:10.1177/1753193411406479.
   Google Scholar
• Mohammed, W. M., B. Ramis Ferrer, S. Iarovyi, E. Negri, L. Fumagalli, A. Lobov, and J. Martinez Lastra. 2017. “Generic Platform for Manufacturing Execution System Functions in Knowledge-Driven Manufacturing Systems.” International Journal of Computer Integrated Manufacturing 31 (3): 262–274.
   Web of Science ®Google Scholar
• Möller, D. P. F. 2016. “Digital Manufacturing/Industry 4.0..” In Guide to Computing Fundamentals in Cyber-Physical Systems, 307–375.
   Google Scholar
• Monostori, L. 2014. “Cyber-Physical Production Systems: Roots, Expectations and R&D Challenges.” In Proceedings of the 47th CIRP Conference on Manufacturing Systems 17: 9–13.
   Google Scholar
• Negri, E., L. Fumagalli, M. Macchi, and M. Garetti 2015a. “Ontology for Service-Based Control of Production Systems.” In S. Umeda, M. Nakano, H. Mizuyama, H. Hibino, D. Kiritsis, and G. von Cieminski (Eds.) IFIP Int. Conf. on Advances in Production Management Systems (APMS), Japan, 484–492.
   Google Scholar
• Negri, E., L. Fumagalli, M. Garetti, and L. Tanca. 2015. “Requirements and Languages for the Semantic Representation of Manufacturing Systems.” Computers in Industry 81 (C): 55–66. doi:10.1016/j.compind.2015.10.009.
   Google Scholar
• Negri, E., L. Fumagalli, and M. Macchi 2017. “A Review of the Roles of Digital Twin in CPS-based Production Systems.” In Proceedings of the 27th Int. Conf. on Flexible Automation and Intelligent Manufacturing (FAIM2017), Italy. Vol 11, 939–948.
   Google Scholar
• Negri, E., S. Perotti, L. Fumagalli, G. Marchet, and M. Garetti. 2017. “Modelling Internal Logistics Systems Through Ontologies.” Journal on Computers in Industry 88 (C): 19–34. doi:10.1016/j.compind.2017.03.004.
   Google Scholar
• Neuhaus, H., and M. Compton 2009. “The Semantic Sensor Network Ontology: A Generic Language to Describe Sensor Assets.” In Proceedings of the AGILE Workshop: Challenges in Geospatial Data Harmonization, hannover, Germany.
   Google Scholar
• NIST Statistics. 2012. “NIST Engineering Statistics Handbook. Introduction to Time Series Analysis.” Accessed May 2018. https://bit.ly/2H0CQTv
   Google Scholar
• oneM2M. 2018, March. “oneM2M Technical Specification: Base Ontology.”
   Google Scholar
• OPC Foundation. 2016. “OPC Unified Architecture: Interoperability for Industrie 4.0 And the Internet of Things.” https://bit.ly/29hTRZw
   Google Scholar
• Oracle. 2017. “Oracle: Digital Twin for IoT Applications: A Comprehensive Approach to Implementing IoT Digital Twin.” Oracle White Paper. https://bit.ly/2IZfFyY
   Google Scholar
• Oussous, A., F.-Z. Benjelloun, A. Ait Lahcen, and S. Belfkih. 2017. “Big Data Technologies: A Survey.” Journal of King Saud University - Computer and Information Sciences, 30 (4): 431-448. http://dx.doi.org/10.1016/j.jksuci.2017.06.001
   Google Scholar
• Overton, J., and J.-C. Brigham. 2017. “The Digital Twin. Data-Driven Simulations Innovate the Manufacturing Process.” White paper. Accessed 26 May 2018 https://bit.ly/2xton2W
   Google Scholar
• Prasad, B. R., and S. Agarwal. 2016. “Comparative Study of Big Data Computing and Storage Tools: A Review.” International Journal of Database Theory and Application 9: 45–66. doi:10.14257/ijdta.2016.9.1.05.
   Google Scholar
• Pratt, M. 2001. “Introduction to ISO10303 the STEP Standard for Product Data Exchange.” Journal of Computing and Information Science in Engineer 1 (1): 102–103. doi:10.1115/1.1354995.
   Google Scholar
• Predix. 2018. “PREDIX the Industrial IoT Application Platform.” Technical Brief. Accessed 26 May 2018. https://invent.ge/2LCgwmO
   Google Scholar
• PTC Windchill. 2018. “Windchill, from Requirements to Quality and from Manufacturing to Services.” https://bit.ly/2LM4BDd
   Google Scholar
• Qiu, W., and A. Bandara 2015. “GPS Trace Mining for Discovering Behavior Patterns.” In Proceedings of the 2015 International Conference on Intelligent Environments. IEEE Computer Society, USA, pp. 65–72. doi: 10.1109/IE.2015.17.
   Google Scholar
• Rajkumar, R., I. Lee, L. Sha, and J. Stankovic 2010. “Cyber-Physical Systems: The Next Computing Revolution.” In Proceedings of the 47th Design Automation Conference (DAC), Anaheim, California, USA, pp. 731–736.
   Google Scholar
• Rios, J., J. C. Hernandez, M. Oliva, and F. Mas 2015. “Product Avatar as Digital Counterpart of a Physical Individual Product: Literature Review and Implications in an Aircraft System.” In Proceedings of the 22nd International Conference on Concurrent Engineering (ISPE CE2015), Vol. 2 of Advances in Transdisciplinary Engineering, 657–666. doi: 10.3233/978-1-61499-544-9-657.
   Google Scholar
• Rodríguez-García, M. Á., R. Valencia-García, F. García-Sánchez, and J. J. Samper-Zapater. 2014. “Ontology-Based Annotation and Retrieval of Services in the Cloud.” Knowledge-Based Systems 56 (C): 15–25. doi:10.1016/j.knosys.2013.10.006.
   Google Scholar
• Rosen, R., G. von Wichert, G. Lo, and K. D. Bettenhausen. 2015. “About the Importance of Autonomy and Digital Twins for the Future of Manufacturing.” In Proceedings of the 15th IFAC Symposium on Information Control Problems in Manufacturing (INCOM 2015) 48 (3): 567–572.
   Google Scholar
• Russomanno, D., C. Kothari, and O. Thomas. 2005. “Building A Sensor Ontology: A Practical Approach Leveraging ISO and OGC Models.” In Proceedings of the 2005 International Conference on Artificial Intelligence (ICAI 2005), Las Vegas, Nevada, USA. Vol. 2, pp. 637–643.
   Google Scholar
• Sarma, S., D. L. Brock, and K. Ashton 2000. “The Networked Physical World.” Proposals for Engineering the Next Generation of Computing, Commerce & Automatic-Identification. White paper. https://bit.ly/2sknSU5
   Google Scholar
• Schleich, B., N. Anwer, L. Mathieu, and S. Wartzack. 2017. “Shaping the Digital Twin for Design and Production Engineering.” In CIRP Annals, Manufacturing Technol. 6 (1): 141–144. doi:10.1016/j.cirp.2017.04.040.
   Google Scholar
• Schlenoff, C., M. Grüninger, M. Ciocoiu, and J. Lee. 2000. “The Essence of the Process Specification Language.” Transactions of the Society for Computer Simulation 16 (4) :204–216.
   Google Scholar
• Schluse, M., and J. Rossmann 2016. “From Simulation to Experimentable Digital Twins - Simulation-Based Development and Operation of Complex Technical Systems.” In Proceedings of the 2nd IEEE International Symposium on Systems Engineering (ISSE 2016), pp. 1–6, doi: 10.1109/SysEng.2016.7753162.
   Google Scholar
• Schroeder, G., C. Steinmetz, C. Pereira, and D. Espindola. 2016. “Digital Twin Data Modeling with AutomationML and a Communication Methodology for Data Exchange.” In International Federation of Automatic Control Symposium on Telematics Applications (TA 2016) 49 (30): 12–17. doi:10.1016/j.ifacol.2016.11.115.
   Google Scholar
• Serpanos, D. 2018. “The Cyber-Physical Systems Revolution.” In Computer 51 (3): 70–73. doi:10.1109/MC.2018.1731058.
   Web of Science ®Google Scholar
• Shafto, M., M. Conroy, R. Doyle, E. Glaessgen, C. Kemp, J. LeMoigne, and L. Wang. 2010. “DRAFT Modeling, Simulation, Information Technology & Processing Roadmap. Technology Area 11".NASA. Online: https://www.nasa.gov/pdf/501321main_TA11-MSITP-DRAFT-Nov2010-A1.pdf
   Google Scholar
• Siemens Simcenter. 2017. “Predict Performance of Your 3D Geometry-Based Design.” https://sie.ag/2xxfWUA
   Google Scholar
• Smith, J. W., and I. Sommerville 2011. “Workload Classification & Software Energy Measurement for Efficient Scheduling on Private Cloud Platforms.” In Proceedings of the ACM SOCC 2011. Available: https://arxiv.org/pdf/1105.2584.pdf
   Google Scholar
• Sutton, R., and A. Barto. 2012. Reinforcement Learning: An Introduction. Cambridge: MIT Press.
   Google Scholar
• Szilagyi, I., and P. Wira 2016. “Ontologies and Semantic Web for the Internet of Things - A Survey.” In Proceedings of the 42nd IEEE Industrial Electronics Society Conference (IECON 2016), Florence, Italy, pp. 6949-6954. doi:10.1109/IECON.2016.7793744).
   Google Scholar
• Taibi, D., V. Lenarduzzi, and C. Pahl. 2017. “Processes, Motivations, and Issues for Migrating to Microservices Architectures: An Empirical Investigation.” IEEE Cloud Computing 4 (5): 22–32. doi:10.1109/mcc.2017.4250931.
   Web of Science ®Google Scholar
• Tao, F., H. Zhang, A. Liu, and A. Y. C. Nee. 2019. “Digital Twin in Industry: State-of-the-art.” IEEE Transactions on Industrial Informatics 15 (4): 2405-2415. doi:10.1109/TII.2018.2873186.
   Web of Science ®Google Scholar
• Tao, F., J. Cheng, Q. Qi, M. Zhang, H. Zhang, and F. Sui. 2017. “Digital Twin-Driven Product Design, Manufacturing and Service with Big Data.” International Journal of Advanced Manufacturing Technology 94 (9–12): 3563–3576. doi:10.1007/s00170-017-0233-1.
   Web of Science ®Google Scholar
• Tavčar, J., and I. Horváth. 2018. “A Review of the Principles of Designing Smart Cyber-Physical Systems for Run-Time Adaptation: Learned Lessons and Open Issues.” IEEE Transactions on Systems, Man, and Cybernetics: Systems. doi:10.1109/TSMC.2018.2814539.
   Web of Science ®Google Scholar
• Taylor, G. W., and G. E. Hinton 2009. “Factored Conditional Restricted Boltzmann Machines for Modelling Motion Style.” In Proc. of the 26th Annual International Conference on Machine Learning (ICML ‘09). ACM, 1025–1032. doi:10.1016/j.actbio.2009.09.014.
   Google Scholar
• Tsoukatos, I., and D. Gunopulos 2001. “Efficient Mining of Spatiotemporal Patterns.” In Proceedings of the International Symposium on Spatial and Temporal Databases (SSTD), Redondo Beach, Los Angeles, CA.pp. 425-442.
   Google Scholar
• Uhlemann, T. H.-J., C. Schock, C. Lehmann, S. Freiberger, and R. Steinhilper. 2017. “The Digital Twin: Demonstrating the Potential of Real Time Data Acquisition in Production Systems.” In Proceedings of the 7th Conference on Learning Factories, CLF 2017 9: 113–120. doi:10.1016/j.promfg.2017.04.043.
   Google Scholar
• Usha, D., and A. P. S. Aslin Jenil. 2014. “A Survey of Big Data Processing in Perspective of Hadoop and MapReduce.” International Journal of Current Engineering and Technology, Vol 4 (2), pp.602-606.
   Google Scholar
• Von Euler-Chelpin, A. 2008. “Information Modelling for the Manufacturing System Life Cycle.” Doctoral Thesis, KTH Royal Institute of Technology, Sweden.
   Google Scholar
• W3C TAG. 2018. “Guidelines for Creating Web Platform Compatible Components.” W3C Technical Architecture Group (TAG). Accessed February 2019. https://www.w3.org/2001/tag/doc/webcomponents-design-guidelines/
   Google Scholar
• Wang, S., J. Wan, D. Li, and C. Zhang. 2016. “Implementing Smart Factory of Industrie 4.0: An Outlook.” International Journal of Distributed Sensor Networks, no. 4: 1–10. doi:10.1155/2016/3159805.
   Google Scholar
• Weyer, S., T. Meyer, M. Ohmer, D. Gorecky, and D. Zühlke 2016. “Future Modeling and Simulation of CPS-based Factories: An Example from the Automotive Industry.” In Proceedings of the IFAC (International Federation of Automatic Control) Conference, 97–102. doi:10.1177/1753193415618128.
   Google Scholar
• White, T. 2012. Hadoop: The Definitive Guide. O’Reilly Media, Inc., Sebastopol, CA, USA.
   Google Scholar
• Yang, H., Z. Luan, W. Li, and D. Qian. 2012. “MapReduce Workload Modeling with Statistical Approach.” Journal on Grid Computing 10 (2): 279–310. doi:10.1007/s10723-011-9201-4.
   Web of Science ®Google Scholar
• Yoon, J.-S., S.-J. Shin, and S.-H. Suh. 2012. “A Conceptual Framework for the Ubiquitous Factory.” International Journal of Production Research 50 (8): 2174–2189. doi:10.1080/00207543.2011.562563.
   Web of Science ®Google Scholar
• Young, R. I. M., A. G. Gunendran, A. F. Cutting-Decelle, and M. Gruninger. 2007. “Manufacturing Knowledge Sharing in PLM: A Progression Towards the Use of Heavy Weight Ontologies.” International Journal of Production Research 45 (7): 1505–1519. doi:10.1080/00207540600942268.
   Web of Science ®Google Scholar
• Zhang, P., J. K. Liu, F. R. Yu, M. Sookhak, M. H. Au, and X. Luo. 2018. “A Survey on Access Control in Fog Computing.” IEEE Communications Magazine 56 (2): 144–149. doi:10.1109/MCOM.2018.1700333.
   Web of Science ®Google Scholar
• Zuehlke, D. 2010. “SmartFactory - Towards a Factory-of-Things.” In Annual Review in Control 34: 129–138. doi:10.1016/j.arcontrol.2010.02.008.
   Web of Science ®Google Scholar
• ZVEI. 2015. “Reference Architectural Model Industrie 4.0 (RAMI 4.0).” Status Report. https://bit.ly/2L66o4J
   Google Scholar